{"entity": "researcher", "timestamp": "2026-08-20T20:28:36.729Z", "family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "affiliations": [], "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b"}}, "publications": [{"entity": "publication", "iuid": "b580045770084598aff068459c95b44e", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/b580045770084598aff068459c95b44e.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/b580045770084598aff068459c95b44e"}}, "title": "Pairwise Attention: Leveraging Mass Differences to Enhance De Novo Sequencing of Mass Spectra.", "authors": [{"family": "Lapin", "given": "Joel", "initials": "J"}, {"family": "Nilsson", "given": "Alfred", "initials": "A"}, {"family": "Wilhelm", "given": "Mathias", "initials": "M", "orcid": "0000-0002-9224-3258", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2eda8473072c48639cbd09676ed17cfe.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "journal article", "published": "2025-07-04", "journal": {"title": "J. Proteome Res.", "issn": "1535-3907", "volume": "24", "issue": "7", "pages": "3722-3730", "issn-l": "1535-3893"}, "abstract": "A fundamental challenge in mass spectrometry-based proteomics is determining which peptide generated a given MS2 spectrum. Peptide sequencing typically relies on matching spectra against a known sequence database, which in some applications is not available. Deep learning-based de novo sequencing can address this limitation by directly predicting peptide sequences from MS2 data. We have seen the application of the transformer architecture to de novo sequencing produce state-of-the-art results on the so-called nine-species benchmark. In this study, we propose an improved transformer encoder inspired by the heuristics used in the manual interpretation of spectra. We modify the attention mechanism with a learned bias based on pairwise mass differences, termed Pairwise Attention (PA). Adding PA improves average peptide precision at 100% coverage by 12.7% (5.9 percentage points) over our base transformer on the original nine-species benchmark. We have also achieved a 7.4% increase over the previously published model Casanovo. Our MS2 encoding strategy is largely orthogonal to other transformer-based models encoding MS2 spectra, enabling straightforward integration into existing deep-learning approaches. Our results show that integrating domain-specific knowledge into transformers boosts de novo sequencing performance.", "doi": "10.1021/acs.jproteome.5c00063", "pmid": "40454436", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC12235698"}], "notes": [], "created": "2026-08-20T08:12:03.344Z", "modified": "2026-08-20T08:12:03.429Z"}, {"entity": "publication", "iuid": "ed86cc02c63e46d09350d9ba3702350b", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/ed86cc02c63e46d09350d9ba3702350b.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/ed86cc02c63e46d09350d9ba3702350b"}}, "title": "Open-Source and FAIR Research Software for Proteomics.", "authors": [{"family": "Perez-Riverol", "given": "Yasset", "initials": "Y", "orcid": "0000-0001-6579-6941", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cb4449bad29741b195a7593fc39a769d.json"}}, {"family": "Bittremieux", "given": "Wout", "initials": "W", "orcid": "0000-0002-3105-1359", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/07e740b95ac84bb6ad8f3ff159aece03.json"}}, {"family": "Noble", "given": "William S", "initials": "WS", "orcid": "0000-0001-7283-4715", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/77bfbf9a1a8242b8955c8dd9f5642a8b.json"}}, {"family": "Martens", "given": "Lennart", "initials": "L", "orcid": "0000-0003-4277-658X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/df9a736ba6d04cbdb881a040480bf6f0.json"}}, {"family": "Bilbao", "given": "Aivett", "initials": "A", "orcid": "0000-0003-2985-8249", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2939469149284dee8f3b20bf40c9e2e9.json"}}, {"family": "Lazear", "given": "Michael R", "initials": "MR", "orcid": "0000-0001-5313-4262", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/ebe2629197bf4b53a53a06244b7f1302.json"}}, {"family": "Gr\u00fcning", "given": "Bjorn", "initials": "B", "orcid": "0000-0002-3079-6586", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b2539c92f7e2437782cf04c0c9a23fc8.json"}}, {"family": "Katz", "given": "Daniel S", "initials": "DS", "orcid": "0000-0001-5934-7525", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b3f98d2fb8384d4684bd7e9e93dc3ef1.json"}}, {"family": "MacCoss", "given": "Michael J", "initials": "MJ", "orcid": "0000-0003-1853-0256", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b57b50e580b940cba50310ac37e89603.json"}}, {"family": "Dai", "given": "Chengxin", "initials": "C"}, {"family": "Eng", "given": "Jimmy K", "initials": "JK", "orcid": "0000-0001-6352-6737", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d748f8f4b03940ac81712a0910415b8b.json"}}, {"family": "Bouwmeester", "given": "Robbin", "initials": "R", "orcid": "0000-0001-6807-7029", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cd945733eeaf46d895f9d8799b430d66.json"}}, {"family": "Shortreed", "given": "Michael R", "initials": "MR", "orcid": "0000-0003-4626-0863", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cf4bd1d3f2ed44bf94983b952500e04d.json"}}, {"family": "Audain", "given": "Enrique", "initials": "E"}, {"family": "Sachsenberg", "given": "Timo", "initials": "T", "orcid": "0000-0002-2833-6070", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d5425fd7b0434642b4c6f7aef67b5f23.json"}}, {"family": "Van Goey", "given": "Jeroen", "initials": "J"}, {"family": "Wallmann", "given": "Georg", "initials": "G"}, {"family": "Wen", "given": "Bo", "initials": "B"}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Fondrie", "given": "William E", "initials": "WE", "orcid": "0000-0002-1554-3716", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0605055453fc4d54b057471ae964ca3f.json"}}], "type": "journal article", "published": "2025-05-02", "journal": {"title": "J. Proteome Res.", "issn": "1535-3907", "volume": "24", "issue": "5", "pages": "2222-2234", "issn-l": "1535-3893"}, "abstract": "Scientific discovery relies on innovative software as much as experimental methods, especially in proteomics, where computational tools are essential for mass spectrometer setup, data analysis, and interpretation. Since the introduction of SEQUEST, proteomics software has grown into a complex ecosystem of algorithms, predictive models, and workflows, but the field faces challenges, including the increasing complexity of mass spectrometry data, limited reproducibility due to proprietary software, and difficulties integrating with other omics disciplines. Closed-source, platform-specific tools exacerbate these issues by restricting innovation, creating inefficiencies, and imposing hidden costs on the community. Open-source software (OSS), aligned with the FAIR Principles (Findable, Accessible, Interoperable, Reusable), offers a solution by promoting transparency, reproducibility, and community-driven development, which fosters collaboration and continuous improvement. In this manuscript, we explore the role of OSS in computational proteomics, its alignment with FAIR principles, and its potential to address challenges related to licensing, distribution, and standardization. Drawing on lessons from other omics fields, we present a vision for a future where OSS and FAIR principles underpin a transparent, accessible, and innovative proteomics community.", "doi": "10.1021/acs.jproteome.4c01079", "pmid": "40267229", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC12053954"}], "notes": [], "created": "2026-08-20T08:12:01.116Z", "modified": "2026-08-20T08:12:01.507Z"}, {"entity": "publication", "iuid": "ef47e685f5774fbcb7f34157add464d0", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/ef47e685f5774fbcb7f34157add464d0.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/ef47e685f5774fbcb7f34157add464d0"}}, "title": "How to Train a Postprocessor for Tandem Mass Spectrometry Proteomics Database Search While Maintaining Control of the False Discovery Rate.", "authors": [{"family": "Freestone", "given": "Jack", "initials": "J", "orcid": "0009-0008-2983-6676", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/724eca4dd41a4de8804cd9300644caf9.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Noble", "given": "William Stafford", "initials": "WS", "orcid": "0000-0001-7283-4715", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/77bfbf9a1a8242b8955c8dd9f5642a8b.json"}}, {"family": "Keich", "given": "Uri", "initials": "U", "orcid": "0000-0002-3209-5011", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/45d275c655e5497c8cfa436ea3b8a32b.json"}}], "type": "journal article", "published": "2025-05-02", "journal": {"title": "J. Proteome Res.", "issn": "1535-3907", "volume": "24", "issue": "5", "pages": "2266-2279", "issn-l": "1535-3893"}, "abstract": "Decoy-based methods are a popular choice for the statistical validation of peptide detection in tandem mass spectrometry and proteomics data. Such methods can achieve a substantial boost in statistical power when coupled with postprocessors such as Percolator that use auxiliary features to learn a better-discriminating scoring function. However, we recently showed that Percolator can struggle to control the false discovery rate (FDR) when reporting the list of discovered peptides. To address this problem, we introduce Percolator-RESET, which is an adaptation of our recently developed RESET meta-procedure to the peptide detection problem. Specifically, Percolator-RESET fuses Percolator's iterative SVM training procedure with RESET's general framework to provide valid false discovery rate control. Percolator-RESET operates in both a standard single-decoy mode and a two-decoy mode, with the latter requiring the generation of two decoys per target. We demonstrate that Percolator-RESET controls the FDR in both modes, both theoretically and empirically, while typically reporting only a marginally smaller number of discoveries than Percolator in the single-decoy mode. The two-decoy mode is marginally more powerful than both Percolator and the single-decoy mode and exhibits less variability than the latter.", "doi": "10.1021/acs.jproteome.4c00742", "pmid": "40163043", "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T08:11:52.931Z", "modified": "2026-08-20T08:11:53.066Z"}, {"entity": "publication", "iuid": "23554e8d4bc44a80bc391882eabc44af", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/23554e8d4bc44a80bc391882eabc44af.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/23554e8d4bc44a80bc391882eabc44af"}}, "title": "Pairwise Attention: Leveraging Mass Differences to Enhance De Novo Sequencing of Mass Spectra", "authors": [{"family": "Lapin", "given": "Joel", "initials": "J", "orcid": "0009-0009-5013-238X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/76acb2bd1deb456c9a740e9e5eaaa010.json"}}, {"family": "Nilsson", "given": "Alfred", "initials": "A", "orcid": "0000-0002-3181-3800", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/33c3a0dde79c446b8b42300074ee9a45.json"}}, {"family": "Wilhelm", "given": "Mathias", "initials": "M", "orcid": "0000-0002-9224-3258", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2eda8473072c48639cbd09676ed17cfe.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "posted-content", "published": "2025-04-03", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2025.03.28.645943", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T11:01:57.125Z", "modified": "2026-08-20T11:01:57.284Z"}, {"entity": "publication", "iuid": "21a8d3e13f23496193c8105214eb4439", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/21a8d3e13f23496193c8105214eb4439.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/21a8d3e13f23496193c8105214eb4439"}}, "title": "Author response: Simultaneous polyclonal antibody sequencing and epitope mapping by cryo electron microscopy and mass spectrometry \u2013 a perspective", "authors": [{"family": "Schulte", "given": "Douwe", "initials": "D", "orcid": "0000-0003-0594-0993", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c6ad74fbd500482591b08a885e861caa.json"}}, {"family": "\u0160iborov\u00e1", "given": "Marta", "initials": "M", "orcid": "0000-0002-6879-5247", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3b902ba7871a42aa80297ce50aee55e6.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Snijder", "given": "Joost", "initials": "J", "orcid": "0000-0002-9310-8226", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/eaf244f006c744cea77ba2addf983ff0.json"}}], "type": "peer-review", "published": "2025-03-18", "journal": {"issn-l": null}, "abstract": null, "doi": "10.7554/elife.101322.2.sa0", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T13:51:01.920Z", "modified": "2026-08-20T13:51:01.993Z"}, {"entity": "publication", "iuid": "8770f4bc45d54bcda6091cba4ead9123", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/8770f4bc45d54bcda6091cba4ead9123.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/8770f4bc45d54bcda6091cba4ead9123"}}, "title": "Simultaneous polyclonal antibody sequencing and epitope mapping by cryo electron microscopy and mass spectrometry \u2013 a perspective", "authors": [{"family": "Schulte", "given": "Douwe", "initials": "D", "orcid": "0000-0003-0594-0993", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c6ad74fbd500482591b08a885e861caa.json"}}, {"family": "\u0160iborov\u00e1", "given": "Marta", "initials": "M", "orcid": "0000-0002-6879-5247", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3b902ba7871a42aa80297ce50aee55e6.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Snijder", "given": "Joost", "initials": "J", "orcid": "0000-0002-9310-8226", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/eaf244f006c744cea77ba2addf983ff0.json"}}], "type": "posted-content", "published": "2025-03-18", "journal": {"issn-l": null}, "abstract": null, "doi": "10.7554/elife.101322.2", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T13:51:00.076Z", "modified": "2026-08-20T13:51:00.121Z"}, {"entity": "publication", "iuid": "44870a114cd24900baccd4796b422a86", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/44870a114cd24900baccd4796b422a86.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/44870a114cd24900baccd4796b422a86"}}, "title": "ProHap enables human proteomic database generation accounting for population diversity.", "authors": [{"family": "Va\u0161\u00ed\u010dek", "given": "Jakub", "initials": "J", "orcid": "0000-0003-2340-0560", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/da1faf367e5c42028b5ecdde0f346b46.json"}}, {"family": "Kuznetsova", "given": "Ksenia G", "initials": "KG", "orcid": "0000-0001-7447-4047", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8a07e1c078c64e019aaac124b238877c.json"}}, {"family": "Skiadopoulou", "given": "Dafni", "initials": "D", "orcid": "0000-0001-5572-0070", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/1875dd41dae84e64813089daa83138c6.json"}}, {"family": "Unger", "given": "Lucas", "initials": "L"}, {"family": "Chera", "given": "Simona", "initials": "S", "orcid": "0000-0001-6310-3486", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2bbfcb7c2c8545ef923a005dd39ac44f.json"}}, {"family": "Ghila", "given": "Luiza M", "initials": "LM", "orcid": "0000-0001-7173-6312", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/ad5fb83952714f2c9ee454a34af3270f.json"}}, {"family": "Bandeira", "given": "Nuno", "initials": "N", "orcid": "0000-0001-8385-3655", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/6ef3073f45c14b7291348f2257d503b8.json"}}, {"family": "Nj\u00f8lstad", "given": "P\u00e5l R", "initials": "PR", "orcid": "0000-0003-0304-6728", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0f9b2ded531b4e728c808c7dad460489.json"}}, {"family": "Johansson", "given": "Stefan", "initials": "S", "orcid": "0000-0002-2298-7008", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0e5286d7375241e685d8eab789a3c1de.json"}}, {"family": "Bruckner", "given": "Stefan", "initials": "S", "orcid": "0000-0002-0885-8402", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/6985e8b619de452d8022809ef7c7df6a.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Vaudel", "given": "Marc", "initials": "M", "orcid": "0000-0003-1179-9578", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2596035e48ab48c6a100c6ef81757b4f.json"}}], "type": "journal article", "published": "2025-02-00", "journal": {"title": "Nat. Methods", "issn": "1548-7105", "volume": "22", "issue": "2", "pages": "273-277", "issn-l": "1548-7091"}, "abstract": "Amid the advances in genomics, the availability of large reference panels of human haplotypes is key to account for human diversity within and across populations. However, mass spectrometry-based proteomics does not benefit from this information. To address this gap, we introduce ProHap, a Python-based tool that constructs protein sequence databases from phased genotypes of reference panels. ProHap enables researchers to account for haplotype diversity in proteomic searches.", "doi": "10.1038/s41592-024-02506-0", "pmid": "39653819", "labels": [], "xrefs": [{"db": "pii", "key": "10.1038/s41592-024-02506-0"}], "notes": [], "created": "2026-08-20T09:03:16.989Z", "modified": "2026-08-20T09:03:17.367Z"}, {"entity": "publication", "iuid": "dafbc8d8e2b3458384f7fbd1a1b7611b", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/dafbc8d8e2b3458384f7fbd1a1b7611b.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/dafbc8d8e2b3458384f7fbd1a1b7611b"}}, "title": "Met-ID: An Open-Source Software for Comprehensive Annotation of Multiple On-Tissue Chemical Modifications in MALDI-MSI", "authors": [{"family": "Bj\u00e4rterot", "given": "Patrik", "initials": "P", "orcid": "0000-0002-4350-5530", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0a958cde39e9471881c0282f9d62f39c.json"}}, {"family": "Nilsson", "given": "Anna", "initials": "A"}, {"family": "Shariatgorji", "given": "Reza", "initials": "R", "orcid": "0000-0001-9484-0921", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/76faa76e9dc445a3bbb1f470e9d33a23.json"}}, {"family": "Vallianatou", "given": "Theodosia", "initials": "T", "orcid": "0000-0002-1477-7756", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/4374524ab2c14bd9ae46f904144dea63.json"}}, {"family": "Kaya", "given": "Ibrahim", "initials": "I", "orcid": "0000-0003-3345-5602", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/43885795cb254e2cba6fe8b538fbfaef.json"}}, {"family": "Svenningsson", "given": "Per", "initials": "P", "orcid": "0000-0001-6727-3802", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b01bbacfa24e4b9794734bf1121d1c38.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Andr\u00e9n", "given": "Per E", "initials": "PE", "orcid": "0000-0002-4062-7743", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/f1dd27e8b238475383983480e10099f6.json"}}], "type": "posted-content", "published": "2025-01-27", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2025.01.24.634674", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T11:00:40.199Z", "modified": "2026-08-20T11:00:40.313Z"}, {"entity": "publication", "iuid": "f1d3015bfe124dbb9dd2fb84537c4b57", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/f1d3015bfe124dbb9dd2fb84537c4b57.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/f1d3015bfe124dbb9dd2fb84537c4b57"}}, "title": "Simultaneous polyclonal antibody sequencing and epitope mapping by cryo electron microscopy and mass spectrometry \u2013 a perspective", "authors": [{"family": "Schulte", "given": "Douwe", "initials": "D", "orcid": "0000-0003-0594-0993", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c6ad74fbd500482591b08a885e861caa.json"}}, {"family": "\u0160iborov\u00e1", "given": "Marta", "initials": "M", "orcid": "0000-0002-6879-5247", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3b902ba7871a42aa80297ce50aee55e6.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Snijder", "given": "Joost", "initials": "J", "orcid": "0000-0002-9310-8226", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/eaf244f006c744cea77ba2addf983ff0.json"}}], "type": "posted-content", "published": "2025-01-16", "journal": {"issn-l": null}, "abstract": null, "doi": "10.7554/elife.101322.1", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T13:50:58.087Z", "modified": "2026-08-20T13:50:58.268Z"}, {"entity": "publication", "iuid": "a4ffb040e494401da0c4f28f101292d0", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/a4ffb040e494401da0c4f28f101292d0.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/a4ffb040e494401da0c4f28f101292d0"}}, "title": "quantms: a cloud-based pipeline for quantitative proteomics enables the reanalysis of public proteomics data.", "authors": [{"family": "Dai", "given": "Chengxin", "initials": "C"}, {"family": "Pfeuffer", "given": "Julianus", "initials": "J"}, {"family": "Wang", "given": "Hong", "initials": "H"}, {"family": "Zheng", "given": "Ping", "initials": "P"}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Sachsenberg", "given": "Timo", "initials": "T", "orcid": "0000-0002-2833-6070", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d5425fd7b0434642b4c6f7aef67b5f23.json"}}, {"family": "Demichev", "given": "Vadim", "initials": "V", "orcid": "0000-0002-2424-9412", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2be8ed6154cd48a0a6de55d75ed3ad52.json"}}, {"family": "Bai", "given": "Mingze", "initials": "M"}, {"family": "Kohlbacher", "given": "Oliver", "initials": "O", "orcid": "0000-0003-1739-4598", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9317a8da5d9d4df782158d7555f229eb.json"}}, {"family": "Perez-Riverol", "given": "Yasset", "initials": "Y", "orcid": "0000-0001-6579-6941", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cb4449bad29741b195a7593fc39a769d.json"}}], "type": "journal article", "published": "2024-09-00", "journal": {"title": "Nat. Methods", "issn": "1548-7105", "volume": "21", "issue": "9", "pages": "1603-1607", "issn-l": "1548-7091"}, "abstract": "The volume of public proteomics data is rapidly increasing, causing a computational challenge for large-scale reanalysis. Here, we introduce quantms ( https://quant,ms.org/ ), an open-source cloud-based pipeline for massively parallel proteomics data analysis. We used quantms to reanalyze 83 public ProteomeXchange datasets, comprising 29,354 instrument files from 13,132 human samples, to quantify 16,599 proteins based on 1.03 million unique peptides. quantms is based on standard file formats improving the reproducibility, submission and dissemination of the data to ProteomeXchange.", "doi": "10.1038/s41592-024-02343-1", "pmid": "38965444", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC11399091"}, {"db": "pii", "key": "10.1038/s41592-024-02343-1"}], "notes": [], "created": "2026-08-20T09:03:06.217Z", "modified": "2026-08-20T09:03:06.356Z"}, {"entity": "publication", "iuid": "2a8bf0b967664c4fa51e9244de67c3dc", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/2a8bf0b967664c4fa51e9244de67c3dc.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/2a8bf0b967664c4fa51e9244de67c3dc"}}, "title": "Spatial landmark detection and tissue registration with deep learning.", "authors": [{"family": "Ekvall", "given": "Markus", "initials": "M", "orcid": "0000-0001-6942-0458", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/18a639299c9b4970ab7be3d5f08723e9.json"}}, {"family": "Bergenstr\u00e5hle", "given": "Ludvig", "initials": "L", "orcid": "0000-0002-5108-4481", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/60ea7a079ae04b8896196dafec84a6fc.json"}}, {"family": "Andersson", "given": "Alma", "initials": "A", "orcid": "0000-0002-4773-9975", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/82aebb401f644b2fbd015827dc916078.json"}}, {"family": "Czarnewski", "given": "Paulo", "initials": "P"}, {"family": "Oleg\u00e5rd", "given": "Johannes", "initials": "J", "orcid": "0000-0001-9082-4318", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/bc00fb7e52b44bb3b6dc9a88fc3cfeac.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Lundeberg", "given": "Joakim", "initials": "J", "orcid": "0000-0003-4313-1601", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d9fa47767cd14ef2b9528c8b998cf095.json"}}], "type": "journal article", "published": "2024-04-00", "journal": {"title": "Nat. Methods", "issn": "1548-7105", "volume": "21", "issue": "4", "pages": "673-679", "issn-l": "1548-7091"}, "abstract": "Spatial landmarks are crucial in describing histological features between samples or sites, tracking regions of interest in microscopy, and registering tissue samples within a common coordinate framework. Although other studies have explored unsupervised landmark detection, existing methods are not well-suited for histological image data as they often require a large number of images to converge, are unable to handle nonlinear deformations between tissue sections and are ineffective for z-stack alignment, other modalities beyond image data or multimodal data. We address these challenges by introducing effortless landmark detection, a new unsupervised landmark detection and registration method using neural-network-guided thin-plate splines. Our proposed method is evaluated on a diverse range of datasets including histology and spatially resolved transcriptomics, demonstrating superior performance in both accuracy and stability compared to existing approaches.", "doi": "10.1038/s41592-024-02199-5", "pmid": "38438615", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC11009106"}, {"db": "pii", "key": "10.1038/s41592-024-02199-5"}], "notes": [], "created": "2026-08-20T09:03:01.754Z", "modified": "2026-08-20T09:03:01.917Z"}, {"entity": "publication", "iuid": "e21fa31a73714586ac5e2ce2fdfa9b0b", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/e21fa31a73714586ac5e2ce2fdfa9b0b.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/e21fa31a73714586ac5e2ce2fdfa9b0b"}}, "title": "Automated model building and protein identification in cryo-EM maps.", "authors": [{"family": "Jamali", "given": "Kiarash", "initials": "K", "orcid": "0009-0008-4805-9518", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c2703bac619b45f68cd9b6b0e5258d13.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Zhang", "given": "Rui", "initials": "R", "orcid": "0000-0003-3159-9565", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/48073c47b2d04592b4a2a1090ffdc342.json"}}, {"family": "Brown", "given": "Alan", "initials": "A", "orcid": "0000-0002-0021-0476", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/aa8915cd08984aea9b16cda6484e50b8.json"}}, {"family": "Kimanius", "given": "Dari", "initials": "D"}, {"family": "Scheres", "given": "Sjors H W", "initials": "SHW", "orcid": "0000-0002-0462-6540", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b64851b999fd42f7bf7b25856946dc62.json"}}], "type": "comparative study", "published": "2024-04-00", "journal": {"title": "Nature", "issn": "1476-4687", "volume": "628", "issue": "8007", "pages": "450-457", "issn-l": "0028-0836"}, "abstract": "Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention in three-dimensional computer graphics programs1,2. Here we present ModelAngelo, a machine-learning approach for automated atomic model building in cryo-EM maps. By combining information from the cryo-EM map with information from protein sequence and structure in a single graph neural network, ModelAngelo builds atomic models for proteins that are of similar quality to those generated by human experts. For nucleotides, ModelAngelo builds backbones with similar accuracy to those built by humans. By using its predicted amino acid probabilities for each residue in hidden Markov model sequence searches, ModelAngelo outperforms human experts in the identification of proteins with unknown sequences. ModelAngelo will therefore remove bottlenecks and increase objectivity in cryo-EM structure determination.", "doi": "10.1038/s41586-024-07215-4", "pmid": "38408488", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC11006616"}, {"db": "pii", "key": "10.1038/s41586-024-07215-4"}], "notes": [], "created": "2026-08-20T08:58:50.842Z", "modified": "2026-08-20T08:58:51.027Z"}, {"entity": "publication", "iuid": "e5e7f6b26dbb452db455dfee67f3566a", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/e5e7f6b26dbb452db455dfee67f3566a.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/e5e7f6b26dbb452db455dfee67f3566a"}}, "title": "Pathway analysis through mutual information.", "authors": [{"family": "Jeuken", "given": "Gustavo S", "initials": "GS", "orcid": "0000-0002-4438-2325", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d577077eccfd49fb982fc76be22ccc72.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "journal article", "published": "2024-01-02", "journal": {"title": "Bioinformatics", "issn": "1367-4811", "volume": "40", "issue": "1", "issn-l": "1367-4803"}, "abstract": "In pathway analysis, we aim to establish a connection between the activity of a particular biological pathway and a difference in phenotype. There are many available methods to perform pathway analysis, many of them rely on an upstream differential expression analysis, and many model the relations between the abundances of the analytes in a pathway as linear relationships.\n\nHere, we propose a new method for pathway analysis, MIPath, that relies on information theoretical principles and, therefore, does not model the association between pathway activity and phenotype, resulting in relatively few assumptions. For this, we construct a graph of the data points for each pathway using a nearest-neighbor approach and score the association between the structure of this graph and the phenotype of these same samples using Mutual Information while adjusting for the effects of random chance in each score. The initial nearest neighbor approach evades individual gene-level comparisons, hence making the method scalable and less vulnerable to missing values. These properties make our method particularly useful for single-cell data. We benchmarked our method on several single-cell datasets, comparing it to established and new methods, and found that it produces robust, reproducible, and meaningful scores.\n\nSource code is available at https://github.com/statisticalbiotechnology/mipath, or through Python Package Index as \"mipathway.\"", "doi": "10.1093/bioinformatics/btad776", "pmid": "38195928", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC10783954"}, {"db": "pii", "key": "7513687"}], "notes": [], "created": "2026-08-20T09:39:47.619Z", "modified": "2026-08-20T09:39:47.714Z"}, {"entity": "publication", "iuid": "d8d32ba10e7242a7afcabad8153667dd", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/d8d32ba10e7242a7afcabad8153667dd.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/d8d32ba10e7242a7afcabad8153667dd"}}, "title": "Semi-supervised Learning While Controlling the FDR with an Application to Tandem Mass Spectrometry Analysis", "authors": [{"family": "Freestone", "given": "Jack", "initials": "J"}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Noble", "given": "William Stafford", "initials": "WS", "orcid": "0000-0001-7283-4715", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/77bfbf9a1a8242b8955c8dd9f5642a8b.json"}}, {"family": "Keich", "given": "Uri", "initials": "U", "orcid": "0000-0002-3209-5011", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/45d275c655e5497c8cfa436ea3b8a32b.json"}}], "type": "book-chapter", "published": "2024-00-00", "journal": {"issn": "0302-9743", "pages": "448-453", "issn-l": null}, "abstract": null, "doi": "10.1007/978-1-0716-3989-4_50", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T06:36:35.884Z", "modified": "2026-08-20T06:36:36.046Z"}, {"entity": "publication", "iuid": "f5131ad6484247fd9eb5ae3ed7addc96", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/f5131ad6484247fd9eb5ae3ed7addc96.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/f5131ad6484247fd9eb5ae3ed7addc96"}}, "title": "ProHap enables proteomic database generation accounting for population diversity", "authors": [{"family": "Va\u0161\u00ed\u010dek", "given": "Jakub", "initials": "J", "orcid": "0000-0003-2340-0560", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/da1faf367e5c42028b5ecdde0f346b46.json"}}, {"family": "Kuznetsova", "given": "Ksenia G", "initials": "KG", "orcid": "0000-0001-7447-4047", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8a07e1c078c64e019aaac124b238877c.json"}}, {"family": "Skiadopoulou", "given": "Dafni", "initials": "D", "orcid": "0000-0001-5572-0070", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/1875dd41dae84e64813089daa83138c6.json"}}, {"family": "Nj\u00f8lstad", "given": "P\u00e5l R", "initials": "PR", "orcid": "0000-0003-0304-6728", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0f9b2ded531b4e728c808c7dad460489.json"}}, {"family": "Johansson", "given": "Stefan", "initials": "S", "orcid": "0000-0002-2298-7008", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0e5286d7375241e685d8eab789a3c1de.json"}}, {"family": "Bruckner", "given": "Stefan", "initials": "S", "orcid": "0000-0002-0885-8402", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/6985e8b619de452d8022809ef7c7df6a.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Vaudel", "given": "Marc", "initials": "M", "orcid": "0000-0003-1179-9578", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2596035e48ab48c6a100c6ef81757b4f.json"}}], "type": "posted-content", "published": "2023-12-24", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2023.12.24.572591", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:51:19.244Z", "modified": "2026-08-20T10:51:19.346Z"}, {"entity": "publication", "iuid": "9d333934ebfe464798b4df7094016b3d", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/9d333934ebfe464798b4df7094016b3d.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/9d333934ebfe464798b4df7094016b3d"}}, "title": "How to train a post-processor for tandem mass spectrometry proteomics database search while maintaining control of the false discovery rate", "authors": [{"family": "Freestone", "given": "Jack", "initials": "J", "orcid": "0009-0008-2983-6676", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/724eca4dd41a4de8804cd9300644caf9.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Noble", "given": "William Stafford", "initials": "WS", "orcid": "0000-0001-7283-4715", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/77bfbf9a1a8242b8955c8dd9f5642a8b.json"}}, {"family": "Keich", "given": "Uri", "initials": "U", "orcid": "0000-0002-3209-5011", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/45d275c655e5497c8cfa436ea3b8a32b.json"}}], "type": "posted-content", "published": "2023-10-31", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2023.10.26.564068", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:48:37.881Z", "modified": "2026-08-20T10:48:37.958Z"}, {"entity": "publication", "iuid": "3ac9d6f4c7f747bcb5eb79b3b456ce7e", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/3ac9d6f4c7f747bcb5eb79b3b456ce7e.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/3ac9d6f4c7f747bcb5eb79b3b456ce7e"}}, "title": "Retention Time and Fragmentation Predictors Increase Confidence in Identification of Common Variant Peptides.", "authors": [{"family": "Skiadopoulou", "given": "Dafni", "initials": "D", "orcid": "0000-0001-5572-0070", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/1875dd41dae84e64813089daa83138c6.json"}}, {"family": "Va\u0161\u00ed\u010dek", "given": "Jakub", "initials": "J"}, {"family": "Kuznetsova", "given": "Ksenia", "initials": "K"}, {"family": "Bouyssi\u00e9", "given": "David", "initials": "D", "orcid": "0000-0002-0847-4759", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/877b0a0677fb463b829241dc4fc52203.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Vaudel", "given": "Marc", "initials": "M", "orcid": "0000-0003-1179-9578", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2596035e48ab48c6a100c6ef81757b4f.json"}}], "type": "journal article", "published": "2023-10-06", "journal": {"title": "J. Proteome Res.", "issn": "1535-3907", "volume": "22", "issue": "10", "pages": "3190-3199", "issn-l": "1535-3893"}, "abstract": "Precision medicine focuses on adapting care to the individual profile of patients, for example, accounting for their unique genetic makeup. Being able to account for the effect of genetic variation on the proteome holds great promise toward this goal. However, identifying the protein products of genetic variation using mass spectrometry has proven very challenging. Here we show that the identification of variant peptides can be improved by the integration of retention time and fragmentation predictors into a unified proteogenomic pipeline. By combining these intrinsic peptide characteristics using the search-engine post-processor Percolator, we demonstrate improved discrimination power between correct and incorrect peptide-spectrum matches. Our results demonstrate that the drop in performance that is induced when expanding a protein sequence database can be compensated, hence enabling efficient identification of genetic variation products in proteomics data. We anticipate that this enhancement of proteogenomic pipelines can provide a more refined picture of the unique proteome of patients and thereby contribute to improving patient care.", "doi": "10.1021/acs.jproteome.3c00243", "pmid": "37656829", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC10563157"}], "notes": [], "created": "2026-08-20T08:11:48.966Z", "modified": "2026-08-20T08:11:49.136Z"}, {"entity": "publication", "iuid": "aab16dd656aa430cb47450fac81f6274", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/aab16dd656aa430cb47450fac81f6274.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/aab16dd656aa430cb47450fac81f6274"}}, "title": "Triqler for Protein Summarization of Data from Data-Independent Acquisition Mass Spectrometry.", "authors": [{"family": "Truong", "given": "Patrick", "initials": "P"}, {"family": "The", "given": "Matthew", "initials": "M", "orcid": "0000-0002-5401-5553", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9d8d7d850ed24f92b9506b203ca63ed1.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "journal article", "published": "2023-04-07", "journal": {"title": "J. Proteome Res.", "issn": "1535-3907", "volume": "22", "issue": "4", "pages": "1359-1366", "issn-l": "1535-3893"}, "abstract": "A frequent goal, or subgoal, when processing data from a quantitative shotgun proteomics experiment is a list of proteins that are differentially abundant under the examined experimental conditions. Unfortunately, obtaining such a list is a challenging process, as the mass spectrometer analyzes the proteolytic peptides of a protein rather than the proteins themselves. We have previously designed a Bayesian hierarchical probabilistic model, Triqler, for combining peptide identification and quantification errors into probabilities of proteins being differentially abundant. However, the model was developed for data from data-dependent acquisition. Here, we show that Triqler is also compatible with data-independent acquisition data after applying minor alterations for the missing value distribution. Furthermore, we find that it has better performance than a set of compared state-of-the-art protein summarization tools when evaluated on data-independent acquisition data.", "doi": "10.1021/acs.jproteome.2c00607", "pmid": "36988210", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC10088044"}], "notes": [], "created": "2026-08-20T08:11:42.307Z", "modified": "2026-08-20T08:11:42.435Z"}, {"entity": "publication", "iuid": "772681df37b54f1e84504f3cc0fd0e98", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/772681df37b54f1e84504f3cc0fd0e98.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/772681df37b54f1e84504f3cc0fd0e98"}}, "title": "Retention time and fragmentation predictors increase confidence in variant peptide identification", "authors": [{"family": "Skiadopoulou", "given": "Dafni", "initials": "D", "orcid": "0000-0001-5572-0070", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/1875dd41dae84e64813089daa83138c6.json"}}, {"family": "Va\u0161\u00ed\u010dek", "given": "Jakub", "initials": "J", "orcid": "0000-0003-2340-0560", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/da1faf367e5c42028b5ecdde0f346b46.json"}}, {"family": "Kuznetsova", "given": "Ksenia", "initials": "K", "orcid": "0000-0001-7447-4047", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8a07e1c078c64e019aaac124b238877c.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Vaudel", "given": "Marc", "initials": "M", "orcid": "0000-0003-1179-9578", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2596035e48ab48c6a100c6ef81757b4f.json"}}], "type": "posted-content", "published": "2023-04-01", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2023.03.29.534843", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:45:05.589Z", "modified": "2026-08-20T10:45:05.665Z"}, {"entity": "publication", "iuid": "75d22281ae0c460ab81945d4b6549abe", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/75d22281ae0c460ab81945d4b6549abe.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/75d22281ae0c460ab81945d4b6549abe"}}, "title": "Toward an Integrated Machine Learning Model of a Proteomics Experiment.", "authors": [{"family": "Neely", "given": "Benjamin A", "initials": "BA", "orcid": "0000-0001-6120-7695", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/6942cadc06104793927194f19aa57a8d.json"}}, {"family": "Dorfer", "given": "Viktoria", "initials": "V", "orcid": "0000-0002-5332-5701", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b2a0a15b0b2945238e7a39343b5c2a29.json"}}, {"family": "Martens", "given": "Lennart", "initials": "L", "orcid": "0000-0003-4277-658X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/df9a736ba6d04cbdb881a040480bf6f0.json"}}, {"family": "Bludau", "given": "Isabell", "initials": "I"}, {"family": "Bouwmeester", "given": "Robbin", "initials": "R", "orcid": "0000-0001-6807-7029", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cd945733eeaf46d895f9d8799b430d66.json"}}, {"family": "Degroeve", "given": "Sven", "initials": "S", "orcid": "0000-0001-8349-3370", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/99e10b1c63144945aa258d810ddbb090.json"}}, {"family": "Deutsch", "given": "Eric W", "initials": "EW", "orcid": "0000-0001-8732-0928", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2463c206245a4dbb979cad9d201d73c4.json"}}, {"family": "Gessulat", "given": "Siegfried", "initials": "S"}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Palczynski", "given": "Pawel", "initials": "P"}, {"family": "Payne", "given": "Samuel H", "initials": "SH", "orcid": "0000-0002-8351-1994", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/fe701ec4cf24456980c1902ec61a0ab1.json"}}, {"family": "Rehfeldt", "given": "Tobias Greisager", "initials": "TG", "orcid": "0000-0002-1190-9485", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9671e5e2b13f40e293e935c355e68d2a.json"}}, {"family": "Schmidt", "given": "Tobias", "initials": "T", "orcid": "0000-0002-1883-6514", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d612bc6bfdce4e968b76abbd88a7603d.json"}}, {"family": "Schw\u00e4mmle", "given": "Veit", "initials": "V", "orcid": "0000-0002-9708-6722", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/158e08b0cfd34f90882f66142d8e62b7.json"}}, {"family": "Uszkoreit", "given": "Julian", "initials": "J", "orcid": "0000-0001-7522-4007", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/97c6efaaa4f045a7a718ca2ba376f641.json"}}, {"family": "Vizca\u00edno", "given": "Juan Antonio", "initials": "JA", "orcid": "0000-0002-3905-4335", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/81245410f3234e658147bc94f6b3dad2.json"}}, {"family": "Wilhelm", "given": "Mathias", "initials": "M", "orcid": "0000-0002-9224-3258", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2eda8473072c48639cbd09676ed17cfe.json"}}, {"family": "Palmblad", "given": "Magnus", "initials": "M", "orcid": "0000-0002-5865-8994", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/80053e2256cd4e55afc7ba916821602c.json"}}], "type": "journal article", "published": "2023-03-03", "journal": {"title": "J. Proteome Res.", "issn": "1535-3907", "volume": "22", "issue": "3", "pages": "681-696", "issn-l": "1535-3893"}, "abstract": "In recent years machine learning has made extensive progress in modeling many aspects of mass spectrometry data. We brought together proteomics data generators, repository managers, and machine learning experts in a workshop with the goals to evaluate and explore machine learning applications for realistic modeling of data from multidimensional mass spectrometry-based proteomics analysis of any sample or organism. Following this sample-to-data roadmap helped identify knowledge gaps and define needs. Being able to generate bespoke and realistic synthetic data has legitimate and important uses in system suitability, method development, and algorithm benchmarking, while also posing critical ethical questions. The interdisciplinary nature of the workshop informed discussions of what is currently possible and future opportunities and challenges. In the following perspective we summarize these discussions in the hope of conveying our excitement about the potential of machine learning in proteomics and to inspire future research.", "doi": "10.1021/acs.jproteome.2c00711", "pmid": "36744821", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC9990124"}], "notes": [], "created": "2026-08-20T08:11:44.566Z", "modified": "2026-08-20T08:11:45.110Z"}, {"entity": "publication", "iuid": "75c6fd13095a4c8490df8c472f6f2b35", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/75c6fd13095a4c8490df8c472f6f2b35.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/75c6fd13095a4c8490df8c472f6f2b35"}}, "title": "Finding haplotypic signatures in proteins.", "authors": [{"family": "Va\u0161\u00ed\u010dek", "given": "Jakub", "initials": "J", "orcid": "0000-0003-2340-0560", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/da1faf367e5c42028b5ecdde0f346b46.json"}}, {"family": "Skiadopoulou", "given": "Dafni", "initials": "D", "orcid": "0000-0001-5572-0070", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/1875dd41dae84e64813089daa83138c6.json"}}, {"family": "Kuznetsova", "given": "Ksenia G", "initials": "KG", "orcid": "0000-0001-7447-4047", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8a07e1c078c64e019aaac124b238877c.json"}}, {"family": "Wen", "given": "Bo", "initials": "B", "orcid": "0000-0003-2261-3150", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b6303720e4bd46ecbaddc0f1621c8fca.json"}}, {"family": "Johansson", "given": "Stefan", "initials": "S", "orcid": "0000-0002-2298-7008", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0e5286d7375241e685d8eab789a3c1de.json"}}, {"family": "Nj\u00f8lstad", "given": "P\u00e5l R", "initials": "PR", "orcid": "0000-0003-0304-6728", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0f9b2ded531b4e728c808c7dad460489.json"}}, {"family": "Bruckner", "given": "Stefan", "initials": "S", "orcid": "0000-0002-0885-8402", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/6985e8b619de452d8022809ef7c7df6a.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Vaudel", "given": "Marc", "initials": "M", "orcid": "0000-0003-1179-9578", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2596035e48ab48c6a100c6ef81757b4f.json"}}], "type": "journal article", "published": "2022-12-28", "journal": {"title": "Gigascience", "issn": "2047-217X", "volume": "12", "issn-l": "2047-217X"}, "abstract": "The nonrandom distribution of alleles of common genomic variants produces haplotypes, which are fundamental in medical and population genetic studies. Consequently, protein-coding genes with different co-occurring sets of alleles can encode different amino acid sequences: protein haplotypes. These protein haplotypes are present in biological samples and detectable by mass spectrometry, but they are not accounted for in proteomic searches. Consequently, the impact of haplotypic variation on the results of proteomic searches and the discoverability of peptides specific to haplotypes remain unknown.\n\nHere, we study how common genetic haplotypes influence the proteomic search space and investigate the possibility to match peptides containing multiple amino acid substitutions to a publicly available data set of mass spectra. We found that for 12.42% of the discoverable amino acid substitutions encoded by common haplotypes, 2 or more substitutions may co-occur in the same peptide after tryptic digestion of the protein haplotypes. We identified 352 spectra that matched to such multivariant peptides, and out of the 4,582 amino acid substitutions identified, 6.37% were covered by multivariant peptides. However, the evaluation of the reliability of these matches remains challenging, suggesting that refined error rate estimation procedures are needed for such complex proteomic searches.\n\nAs these procedures become available and the ability to analyze protein haplotypes increases, we anticipate that proteomics will provide new information on the consequences of common variation, across tissues and time.", "doi": "10.1093/gigascience/giad093", "pmid": "37919975", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC10622322"}, {"db": "pii", "key": "7334270"}], "notes": [], "created": "2026-08-20T09:41:38.734Z", "modified": "2026-08-20T09:41:38.884Z"}, {"entity": "publication", "iuid": "0c0378b720fc43d3b9d7ab06cd912cab", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/0c0378b720fc43d3b9d7ab06cd912cab.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/0c0378b720fc43d3b9d7ab06cd912cab"}}, "title": "Finding Haplotypic Signatures in Proteins", "authors": [{"family": "Va\u0161\u00ed\u010dek", "given": "Jakub", "initials": "J", "orcid": "0000-0003-2340-0560", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/da1faf367e5c42028b5ecdde0f346b46.json"}}, {"family": "Skiadopoulou", "given": "Dafni", "initials": "D", "orcid": "0000-0001-5572-0070", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/1875dd41dae84e64813089daa83138c6.json"}}, {"family": "Kuznetsova", "given": "Ksenia G", "initials": "KG", "orcid": "0000-0001-7447-4047", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8a07e1c078c64e019aaac124b238877c.json"}}, {"family": "Wen", "given": "Bo", "initials": "B", "orcid": "0000-0003-2261-3150", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b6303720e4bd46ecbaddc0f1621c8fca.json"}}, {"family": "Johansson", "given": "Stefan", "initials": "S", "orcid": "0000-0002-2298-7008", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0e5286d7375241e685d8eab789a3c1de.json"}}, {"family": "Nj\u00f8lstad", "given": "P\u00e5l R", "initials": "PR", "orcid": "0000-0003-0304-6728", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0f9b2ded531b4e728c808c7dad460489.json"}}, {"family": "Bruckner", "given": "Stefan", "initials": "S", "orcid": "0000-0002-0885-8402", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/6985e8b619de452d8022809ef7c7df6a.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Vaudel", "given": "Marc", "initials": "M", "orcid": "0000-0003-1179-9578", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2596035e48ab48c6a100c6ef81757b4f.json"}}], "type": "posted-content", "published": "2022-11-24", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2022.11.21.517096", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:42:20.368Z", "modified": "2026-08-20T10:42:20.511Z"}, {"entity": "publication", "iuid": "aff78294a8224cb39c1f853a51b99d7b", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/aff78294a8224cb39c1f853a51b99d7b.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/aff78294a8224cb39c1f853a51b99d7b"}}, "title": "Pathway Analysis Through Mutual Information", "authors": [{"family": "Jeuken", "given": "Gustavo S", "initials": "GS", "orcid": "0000-0002-4438-2325", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d577077eccfd49fb982fc76be22ccc72.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "posted-content", "published": "2022-07-02", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2022.06.30.495461", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:12:26.025Z", "modified": "2026-08-20T10:12:26.073Z"}, {"entity": "publication", "iuid": "08ee30650bc34e33bb0b209135396f9e", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/08ee30650bc34e33bb0b209135396f9e.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/08ee30650bc34e33bb0b209135396f9e"}}, "title": "Prosit Transformer: A transformer for Prediction of MS2 Spectrum Intensities.", "authors": [{"family": "Ekvall", "given": "Markus", "initials": "M"}, {"family": "Truong", "given": "Patrick", "initials": "P"}, {"family": "Gabriel", "given": "Wassim", "initials": "W", "orcid": "0000-0001-6440-9794", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3d788a6b62134f5492b2c31aec9a1625.json"}}, {"family": "Wilhelm", "given": "Mathias", "initials": "M", "orcid": "0000-0002-9224-3258", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2eda8473072c48639cbd09676ed17cfe.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "journal article", "published": "2022-05-06", "journal": {"title": "J. Proteome Res.", "issn": "1535-3907", "volume": "21", "issue": "5", "pages": "1359-1364", "issn-l": "1535-3893"}, "abstract": "Machine learning has been an integral part of interpreting data from mass spectrometry (MS)-based proteomics for a long time. Relatively recently, a machine-learning structure appeared successful in other areas of bioinformatics, Transformers. Furthermore, the implementation of Transformers within bioinformatics has become relatively convenient due to transfer learning, i.e., adapting a network trained for other tasks to new functionality. Transfer learning makes these relatively large networks more accessible as it generally requires less data, and the training time improves substantially. We implemented a Transformer based on the pretrained model TAPE to predict MS2 intensities. TAPE is a general model trained to predict missing residues from protein sequences. Despite being trained for a different task, we could modify its behavior by adding a prediction head at the end of the TAPE model and fine-tune it using the spectrum intensity from the training set to the well-known predictor Prosit. We demonstrate that the predictor, which we call Prosit Transformer, outperforms the recurrent neural-network-based predictor Prosit, increasing the median angular similarity on its hold-out set from 0.908 to 0.929. We believe that Transformers will significantly increase prediction accuracy for other types of predictions within MS-based proteomics.", "doi": "10.1021/acs.jproteome.1c00870", "pmid": "35413196", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC9087333"}], "notes": [], "created": "2026-08-20T08:11:24.560Z", "modified": "2026-08-20T08:11:24.708Z"}, {"entity": "publication", "iuid": "0f57550e021d409b9b359cb41520fee2", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/0f57550e021d409b9b359cb41520fee2.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/0f57550e021d409b9b359cb41520fee2"}}, "title": "Putting Humpty Dumpty Back Together Again: What Does Protein Quantification Mean in Bottom-Up Proteomics?", "authors": [{"family": "Plubell", "given": "Deanna L", "initials": "DL", "orcid": "0000-0002-6580-8073", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c353f24426604d199be325edcde06be7.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Webb-Robertson", "given": "Bobbie-Jo", "initials": "BJ"}, {"family": "Bramer", "given": "Lisa M", "initials": "LM", "orcid": "0000-0002-8384-1926", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/e214d736fc5d44d3be3baff22c478df2.json"}}, {"family": "Ives", "given": "Ashley", "initials": "A", "orcid": "0000-0002-1318-5732", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/f27079ba95934664ab1fc288fa121cbf.json"}}, {"family": "Kelleher", "given": "Neil L", "initials": "NL", "orcid": "0000-0002-8815-3372", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/db299d87427049b8972eabe2d9f453a8.json"}}, {"family": "Smith", "given": "Lloyd M", "initials": "LM"}, {"family": "Montine", "given": "Thomas J", "initials": "TJ", "orcid": "0000-0002-1346-2728", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c4a2c2ba8b0d49ccb31bceea9e11206b.json"}}, {"family": "Wu", "given": "Christine C", "initials": "CC"}, {"family": "MacCoss", "given": "Michael J", "initials": "MJ", "orcid": "0000-0003-1853-0256", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b57b50e580b940cba50310ac37e89603.json"}}], "type": "journal article", "published": "2022-04-01", "journal": {"title": "J. Proteome Res.", "issn": "1535-3907", "volume": "21", "issue": "4", "pages": "891-898", "issn-l": "1535-3893"}, "abstract": "Bottom-up proteomics provides peptide measurements and has been invaluable for moving proteomics into large-scale analyses. Commonly, a single quantitative value is reported for each protein-coding gene by aggregating peptide quantities into protein groups following protein inference or parsimony. However, given the complexity of both RNA splicing and post-translational protein modification, it is overly simplistic to assume that all peptides that map to a singular protein-coding gene will demonstrate the same quantitative response. By assuming that all peptides from a protein-coding sequence are representative of the same protein, we may miss the discovery of important biological differences. To capture the contributions of existing proteoforms, we need to reconsider the practice of aggregating protein values to a single quantity per protein-coding gene.", "doi": "10.1021/acs.jproteome.1c00894", "pmid": "35220718", "labels": [], "xrefs": [{"db": "mid", "key": "NIHMS1789966"}, {"db": "pmc", "key": "PMC8976764"}], "notes": [], "created": "2026-08-20T08:11:26.625Z", "modified": "2026-08-20T08:11:26.897Z"}, {"entity": "publication", "iuid": "6b3c9d1faf054f2caf91c423ec008722", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/6b3c9d1faf054f2caf91c423ec008722.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/6b3c9d1faf054f2caf91c423ec008722"}}, "title": "Interpretation of the DOME Recommendations for Machine Learning in Proteomics and Metabolomics.", "authors": [{"family": "Palmblad", "given": "Magnus", "initials": "M", "orcid": "0000-0002-5865-8994", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/80053e2256cd4e55afc7ba916821602c.json"}}, {"family": "B\u00f6cker", "given": "Sebastian", "initials": "S", "orcid": "0000-0002-9304-8091", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c71ab14b72a540f3be202f873d6c7dea.json"}}, {"family": "Degroeve", "given": "Sven", "initials": "S"}, {"family": "Kohlbacher", "given": "Oliver", "initials": "O", "orcid": "0000-0003-1739-4598", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9317a8da5d9d4df782158d7555f229eb.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Noble", "given": "William Stafford", "initials": "WS", "orcid": "0000-0001-7283-4715", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/77bfbf9a1a8242b8955c8dd9f5642a8b.json"}}, {"family": "Wilhelm", "given": "Mathias", "initials": "M", "orcid": "0000-0002-9224-3258", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2eda8473072c48639cbd09676ed17cfe.json"}}], "type": "journal article", "published": "2022-04-01", "journal": {"title": "J. Proteome Res.", "issn": "1535-3907", "volume": "21", "issue": "4", "pages": "1204-1207", "issn-l": "1535-3893"}, "abstract": "Machine learning is increasingly applied in proteomics and metabolomics to predict molecular structure, function, and physicochemical properties, including behavior in chromatography, ion mobility, and tandem mass spectrometry. These must be described in sufficient detail to apply or evaluate the performance of trained models. Here we look at and interpret the recently published and general DOME (Data, Optimization, Model, Evaluation) recommendations for conducting and reporting on machine learning in the specific context of proteomics and metabolomics.", "doi": "10.1021/acs.jproteome.1c00900", "pmid": "35119864", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC8981311"}], "notes": [], "created": "2026-08-20T08:11:33.301Z", "modified": "2026-08-20T08:11:33.445Z"}, {"entity": "publication", "iuid": "efb21ed87eee482fb9a719e0a432ab50", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/efb21ed87eee482fb9a719e0a432ab50.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/efb21ed87eee482fb9a719e0a432ab50"}}, "title": "Survival analysis of pathway activity as a prognostic determinant in breast cancer.", "authors": [{"family": "Jeuken", "given": "Gustavo S", "initials": "GS", "orcid": "0000-0002-4438-2325", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d577077eccfd49fb982fc76be22ccc72.json"}}, {"family": "Tobin", "given": "Nicholas P", "initials": "NP", "orcid": "0000-0003-2343-9772", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b9aa223903694c8399b89adc231facce.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "journal article", "published": "2022-03-00", "journal": {"title": "PLoS Comput Biol", "issn": "1553-7358", "volume": "18", "issue": "3", "pages": "e1010020", "issn-l": "1553-734X"}, "abstract": "High throughput biology enables the measurements of relative concentrations of thousands of biomolecules from e.g. tissue samples. The process leaves the investigator with the problem of how to best interpret the potentially large number of differences between samples. Many activities in a cell depend on ordered reactions involving multiple biomolecules, often referred to as pathways. It hence makes sense to study differences between samples in terms of altered pathway activity, using so-called pathway analysis. Traditional pathway analysis gives significance to differences in the pathway components' concentrations between sample groups, however, less frequently used methods for estimating individual samples' pathway activities have been suggested. Here we demonstrate that such a method can be used for pathway-based survival analysis. Specifically, we investigate the pathway activities' association with patients' survival time based on the transcription profiles of the METABRIC dataset. Our implementation shows that pathway activities are better prognostic markers for survival time in METABRIC than the individual transcripts. We also demonstrate that we can regress out the effect of individual pathways on other pathways, which allows us to estimate the other pathways' residual pathway activity on survival. Furthermore, we illustrate how one can visualize the often interdependent measures over hierarchical pathway databases using sunburst plots.", "doi": "10.1371/journal.pcbi.1010020", "pmid": "35344554", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC8989354"}, {"db": "pii", "key": "PCOMPBIOL-D-21-01051"}], "notes": [], "created": "2026-08-20T12:43:05.568Z", "modified": "2026-08-20T12:43:05.651Z"}, {"entity": "publication", "iuid": "245bd5639e1f4d64ac139e92715c8495", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/245bd5639e1f4d64ac139e92715c8495.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/245bd5639e1f4d64ac139e92715c8495"}}, "title": "A comprehensive evaluation of consensus spectrum generation methods in proteomics", "authors": [{"family": "Luo", "given": "Xiyang", "initials": "X"}, {"family": "Bittremieux", "given": "Wout", "initials": "W", "orcid": "0000-0002-3105-1359", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/07e740b95ac84bb6ad8f3ff159aece03.json"}}, {"family": "Griss", "given": "Johannes", "initials": "J", "orcid": "0000-0003-2206-9511", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b001048c5a5148bdb9bd16ff46e067db.json"}}, {"family": "Deutsch", "given": "Eric W", "initials": "EW", "orcid": "0000-0001-8732-0928", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2463c206245a4dbb979cad9d201d73c4.json"}}, {"family": "Sachsenberg", "given": "Timo", "initials": "T", "orcid": "0000-0002-2833-6070", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d5425fd7b0434642b4c6f7aef67b5f23.json"}}, {"family": "Levitsky", "given": "Lev I", "initials": "LI", "orcid": "0000-0002-4048-0876", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d992ceb2e30945529ee9200b4fe306c9.json"}}, {"family": "Ivanov", "given": "Mark V", "initials": "MV", "orcid": "0000-0003-4762-2846", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cd0d8592597c43eea8a122dd2ac128b5.json"}}, {"family": "Bubis", "given": "Julia A", "initials": "JA", "orcid": "0000-0002-4895-6146", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/1face4f1b57e4bddafffb09013e3e07c.json"}}, {"family": "Gabriels", "given": "Ralf", "initials": "R", "orcid": "0000-0002-1679-1711", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/30094adc291549c28c6c74cbeb9aacd2.json"}}, {"family": "Webel", "given": "Henry", "initials": "H", "orcid": "0000-0001-8833-7617", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b16b0288b71a4c37a9d3c0cee30a16bf.json"}}, {"family": "Sanchez", "given": "Aniel", "initials": "A", "orcid": "0000-0002-0278-8802", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/e38a8f60ffc14ab18499396cbf8595a8.json"}}, {"family": "Bai", "given": "Mingze", "initials": "M", "orcid": "0000-0002-9782-2056", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/bb01c19bbd9c4a96950d782fc71db8b9.json"}}, {"family": "Kall", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Perez-Riverol", "given": "Yasset", "initials": "Y", "orcid": "0000-0001-6579-6941", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cb4449bad29741b195a7593fc39a769d.json"}}], "type": "posted-content", "published": "2022-01-27", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2022.01.25.477699", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:09:16.755Z", "modified": "2026-08-20T10:09:17.065Z"}, {"entity": "publication", "iuid": "355dec5935654d08b2635417ed746104", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/355dec5935654d08b2635417ed746104.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/355dec5935654d08b2635417ed746104"}}, "title": "Survival analysis of pathway activity as a prognostic determinant in breast cancer", "authors": [{"family": "Jeuken", "given": "Gustavo S", "initials": "GS", "orcid": "0000-0002-4438-2325", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d577077eccfd49fb982fc76be22ccc72.json"}}, {"family": "Tobin", "given": "Nicholas P", "initials": "NP"}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "posted-content", "published": "2021-05-20", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2021.05.19.444688", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:04:10.158Z", "modified": "2026-08-20T10:04:10.228Z"}, {"entity": "publication", "iuid": "16bccfafccd44fe5a9a4c6a6d4992997", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/16bccfafccd44fe5a9a4c6a6d4992997.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/16bccfafccd44fe5a9a4c6a6d4992997"}}, "title": "Triqler for MaxQuant: Enhancing Results from MaxQuant by Bayesian Error Propagation and Integration.", "authors": [{"family": "The", "given": "Matthew", "initials": "M"}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "journal article", "published": "2021-04-02", "journal": {"title": "J. Proteome Res.", "issn": "1535-3907", "volume": "20", "issue": "4", "pages": "2062-2068", "issn-l": "1535-3893"}, "abstract": "Error estimation for differential protein quantification by label-free shotgun proteomics is challenging due to the multitude of error sources, each contributing uncertainty to the final results. We have previously designed a Bayesian model, Triqler, to combine such error terms into one combined quantification error. Here we present an interface for Triqler that takes MaxQuant results as input, allowing quick reanalysis of already processed data. We demonstrate that Triqler outperforms the original processing for a large set of both engineered and clinical/biological relevant data sets. Triqler and its interface to MaxQuant are available as a Python module under an Apache 2.0 license from https://pypi.org/project/triqler/.", "doi": "10.1021/acs.jproteome.0c00902", "pmid": "33661646", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC8041382"}], "notes": [], "created": "2026-08-20T08:11:19.983Z", "modified": "2026-08-20T08:11:20.064Z"}, {"entity": "publication", "iuid": "cf9951bf6e7d4068b34c4a0ed1013912", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/cf9951bf6e7d4068b34c4a0ed1013912.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/cf9951bf6e7d4068b34c4a0ed1013912"}}, "title": "Performing Selection on a Monotonic Function in Lieu of Sorting Using Layer-Ordered Heaps.", "authors": [{"family": "Lucke", "given": "Kyle", "initials": "K"}, {"family": "Pennington", "given": "Jake", "initials": "J"}, {"family": "Kreitzberg", "given": "Patrick", "initials": "P"}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Serang", "given": "Oliver", "initials": "O", "orcid": "0000-0003-1245-7051", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/eac0e723ec744a068eff6f4e55fa5b55.json"}}], "type": "journal article", "published": "2021-04-02", "journal": {"title": "J. Proteome Res.", "issn": "1535-3907", "volume": "20", "issue": "4", "pages": "1849-1854", "issn-l": "1535-3893"}, "abstract": "Nonparametric statistical tests are an integral part of scientific experiments in a diverse range of fields. When performing such tests, it is standard to sort values; however, this requires \u03a9(n log(n)) time to sort n values. Thus given enough data, sorting becomes the computational bottleneck, even with very optimized implementations such as the C++ standard library routine, std::sort. Frequently, a nonparametric statistical test is only used to partition values above and below a threshold in the sorted ordering, where the threshold corresponds to a significant statistical result. Linear-time selection and partitioning algorithms cannot be directly used because the selection and partitioning are performed on the transformed statistical significance values rather than on the sorted statistics. Usually, those transformed statistical significance values (e.g., the p value when investigating the family-wise error rate and q values when investigating the false discovery rate (FDR)) can only be computed at a threshold. Because this threshold is unknown, this leads to sorting the data. Layer-ordered heaps, which can be constructed in O(n), only partially sort values and thus can be used to get around the slow runtime required to fully sort. Here we introduce a layer-ordering-based method for selection and partitioning on the transformed values (e.g., p values or q values). We demonstrate the use of this method to partition peptides using an FDR threshold. This approach is applied to speed up Percolator, a postprocessing algorithm used in mass-spectrometry-based proteomics to evaluate the quality of peptide-spectrum matches (PSMs), by >70% on data sets with 100 million PSMs.", "doi": "10.1021/acs.jproteome.0c00711", "pmid": "33529032", "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T08:11:18.275Z", "modified": "2026-08-20T08:11:18.389Z"}, {"entity": "publication", "iuid": "9b67e9b516cb40128033ab972207b9fa", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/9b67e9b516cb40128033ab972207b9fa.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/9b67e9b516cb40128033ab972207b9fa"}}, "title": "Can we put Humpty Dumpty back together again? What does protein quantification mean in bottom-up proteomics?", "authors": [{"family": "Plubell", "given": "Deanna L", "initials": "DL", "orcid": "0000-0002-6580-8073", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c353f24426604d199be325edcde06be7.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Webb-Robertson", "given": "Bobbie Jo", "initials": "BJ", "orcid": "0000-0002-4744-2397", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b6a368f002a24dd996fecb43b53a6a2c.json"}}, {"family": "Bramer", "given": "Lisa", "initials": "L"}, {"family": "Ives", "given": "Ashley", "initials": "A"}, {"family": "Kelleher", "given": "Neil L", "initials": "NL", "orcid": "0000-0002-8815-3372", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/db299d87427049b8972eabe2d9f453a8.json"}}, {"family": "Smith", "given": "Lloyd M", "initials": "LM"}, {"family": "Montine", "given": "Thomas J", "initials": "TJ"}, {"family": "Wu", "given": "Christine C", "initials": "CC"}, {"family": "MacCoss", "given": "Michael J", "initials": "MJ", "orcid": "0000-0003-1853-0256", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b57b50e580b940cba50310ac37e89603.json"}}], "type": "posted-content", "published": "2021-01-27", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2021.01.25.428175", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:01:15.591Z", "modified": "2026-08-20T10:01:15.707Z"}, {"entity": "publication", "iuid": "d1253eda523c4cbc98feaa68f601faea", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/d1253eda523c4cbc98feaa68f601faea.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/d1253eda523c4cbc98feaa68f601faea"}}, "title": "Parallelized calculation of permutation tests", "authors": [{"family": "Ekvall", "given": "Markus", "initials": "M"}, {"family": "H\u00f6hle", "given": "Michael", "initials": "M", "orcid": "0000-0002-0423-6702", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3ec0b199c0284c2682c3b9908254a7ed.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "posted-content", "published": "2020-10-02", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2020.10.01.321828", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T09:59:21.570Z", "modified": "2026-08-20T09:59:21.671Z"}, {"entity": "publication", "iuid": "2f9a4135ce9b472f857af9618ec81eda", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/2f9a4135ce9b472f857af9618ec81eda.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/2f9a4135ce9b472f857af9618ec81eda"}}, "title": "Integrating identification and quantification uncertainty for differential protein abundance analysis with Triqler", "authors": [{"family": "The", "given": "Matthew", "initials": "M", "orcid": "0000-0002-5401-5553", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9d8d7d850ed24f92b9506b203ca63ed1.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "posted-content", "published": "2020-09-25", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2020.09.24.311605", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T09:59:15.777Z", "modified": "2026-08-20T09:59:15.842Z"}, {"entity": "publication", "iuid": "0555a196a9a04c8bb726263466bbf6e0", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/0555a196a9a04c8bb726263466bbf6e0.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/0555a196a9a04c8bb726263466bbf6e0"}}, "title": "Focus on the spectra that matter by clustering of quantification data in shotgun proteomics.", "authors": [{"family": "The", "given": "Matthew", "initials": "M"}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "journal article", "published": "2020-06-26", "journal": {"title": "Nat Commun", "issn": "2041-1723", "volume": "11", "issue": "1", "pages": "3234", "issn-l": "2041-1723"}, "abstract": "In shotgun proteomics, the analysis of label-free quantification experiments is typically limited by the identification rate and the noise level in the quantitative data. This generally causes a low sensitivity in differential expression analysis. Here, we propose a quantification-first approach for peptides that reverses the classical identification-first workflow, thereby preventing valuable information from being discarded in the identification stage. Specifically, we introduce a method, Quandenser, that applies unsupervised clustering on both MS1 and MS2 level to summarize all analytes of interest without assigning identities. This reduces search time due to the data reduction. We can now employ open modification and de novo searches to identify analytes of interest that would have gone unnoticed in traditional pipelines. Quandenser+Triqler outperforms the state-of-the-art method MaxQuant+Perseus, consistently reporting more differentially abundant proteins for all tested datasets. Software is available for all major operating systems at https://github.com/statisticalbiotechnology/quandenser, under Apache 2.0 license.", "doi": "10.1038/s41467-020-17037-3", "pmid": "32591519", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC7319958"}, {"db": "pii", "key": "10.1038/s41467-020-17037-3"}], "notes": [], "created": "2026-08-20T08:51:07.629Z", "modified": "2026-08-20T08:51:07.690Z"}, {"entity": "publication", "iuid": "2217a0a46f8a48d494c5123c34293e6d", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/2217a0a46f8a48d494c5123c34293e6d.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/2217a0a46f8a48d494c5123c34293e6d"}}, "title": "Speeding Up Percolator.", "authors": [{"family": "Halloran", "given": "John T", "initials": "JT"}, {"family": "Zhang", "given": "Hantian", "initials": "H"}, {"family": "Kara", "given": "Kaan", "initials": "K"}, {"family": "Renggli", "given": "C\u00e9dric", "initials": "C"}, {"family": "The", "given": "Matthew", "initials": "M"}, {"family": "Zhang", "given": "Ce", "initials": "C"}, {"family": "Rocke", "given": "David M", "initials": "DM"}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Noble", "given": "William Stafford", "initials": "WS", "orcid": "0000-0001-7283-4715", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/77bfbf9a1a8242b8955c8dd9f5642a8b.json"}}], "type": "journal article", "published": "2019-09-06", "journal": {"title": "J. Proteome Res.", "issn": "1535-3907", "volume": "18", "issue": "9", "pages": "3353-3359", "issn-l": "1535-3893"}, "abstract": "The processing of peptide tandem mass spectrometry data involves matching observed spectra against a sequence database. The ranking and calibration of these peptide-spectrum matches can be improved substantially using a machine learning postprocessor. Here, we describe our efforts to speed up one widely used postprocessor, Percolator. The improved software is dramatically faster than the previous version of Percolator, even when using relatively few processors. We tested the new version of Percolator on a data set containing over 215 million spectra and recorded an overall reduction to 23% of the running time as compared to the unoptimized code. We also show that the memory footprint required by these speedups is modest relative to that of the original version of Percolator.", "doi": "10.1021/acs.jproteome.9b00288", "pmid": "31407580", "labels": [], "xrefs": [{"db": "mid", "key": "NIHMS1059676"}, {"db": "pmc", "key": "PMC6884961"}], "notes": [], "created": "2026-08-20T08:12:19.090Z", "modified": "2026-08-20T08:12:19.172Z"}, {"entity": "publication", "iuid": "ae1e75a1bfa8462d90a2ca48c163aed2", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/ae1e75a1bfa8462d90a2ca48c163aed2.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/ae1e75a1bfa8462d90a2ca48c163aed2"}}, "title": "Integrated Identification and Quantification Error Probabilities for Shotgun Proteomics.", "authors": [{"family": "The", "given": "Matthew", "initials": "M", "orcid": "0000-0002-5401-5553", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9d8d7d850ed24f92b9506b203ca63ed1.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "journal article", "published": "2019-03-00", "journal": {"title": "Mol. Cell Proteomics", "issn": "1535-9484", "volume": "18", "issue": "3", "pages": "561-570", "issn-l": "1535-9476"}, "abstract": "Protein quantification by label-free shotgun proteomics experiments is plagued by a multitude of error sources. Typical pipelines for identifying differential proteins use intermediate filters to control the error rate. However, they often ignore certain error sources and, moreover, regard filtered lists as completely correct in subsequent steps. These two indiscretions can easily lead to a loss of control of the false discovery rate (FDR). We propose a probabilistic graphical model, Triqler, that propagates error information through all steps, employing distributions in favor of point estimates, most notably for missing value imputation. The model outputs posterior probabilities for fold changes between treatment groups, highlighting uncertainty rather than hiding it. We analyzed 3 engineered data sets and achieved FDR control and high sensitivity, even for truly absent proteins. In a bladder cancer clinical data set we discovered 35 proteins at 5% FDR, whereas the original study discovered 1 and MaxQuant/Perseus 4 proteins at this threshold. Compellingly, these 35 proteins showed enrichment for functional annotation terms, whereas the top ranked proteins reported by MaxQuant/Perseus showed no enrichment. The model executes in minutes and is freely available at https://pypi.org/project/triqler/.", "doi": "10.1074/mcp.RA118.001018", "pmid": "30482846", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC6398204"}, {"db": "pii", "key": "S1535-9476(20)31858-2"}], "notes": [], "created": "2026-08-20T09:32:41.376Z", "modified": "2026-08-20T09:32:41.462Z"}, {"entity": "publication", "iuid": "ea525cca041145b7bdfe210040715780", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/ea525cca041145b7bdfe210040715780.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/ea525cca041145b7bdfe210040715780"}}, "title": "Expanding the Use of Spectral Libraries in Proteomics.", "authors": [{"family": "Deutsch", "given": "Eric W", "initials": "EW", "orcid": "0000-0001-8732-0928", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2463c206245a4dbb979cad9d201d73c4.json"}}, {"family": "Perez-Riverol", "given": "Yasset", "initials": "Y", "orcid": "0000-0001-6579-6941", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cb4449bad29741b195a7593fc39a769d.json"}}, {"family": "Chalkley", "given": "Robert J", "initials": "RJ"}, {"family": "Wilhelm", "given": "Mathias", "initials": "M", "orcid": "0000-0002-9224-3258", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2eda8473072c48639cbd09676ed17cfe.json"}}, {"family": "Tate", "given": "Stephen", "initials": "S"}, {"family": "Sachsenberg", "given": "Timo", "initials": "T", "orcid": "0000-0002-2833-6070", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d5425fd7b0434642b4c6f7aef67b5f23.json"}}, {"family": "Walzer", "given": "Mathias", "initials": "M"}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Delanghe", "given": "Bernard", "initials": "B"}, {"family": "B\u00f6cker", "given": "Sebastian", "initials": "S", "orcid": "0000-0002-9304-8091", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/c71ab14b72a540f3be202f873d6c7dea.json"}}, {"family": "Schymanski", "given": "Emma L", "initials": "EL", "orcid": "0000-0001-6868-8145", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cc533a4744624b80960f4cf28cabdd64.json"}}, {"family": "Wilmes", "given": "Paul", "initials": "P", "orcid": "0000-0002-6478-2924", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/e169727cc0f9482baf98944388a77b24.json"}}, {"family": "Dorfer", "given": "Viktoria", "initials": "V", "orcid": "0000-0002-5332-5701", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b2a0a15b0b2945238e7a39343b5c2a29.json"}}, {"family": "Kuster", "given": "Bernhard", "initials": "B", "orcid": "0000-0002-9094-1677", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5196477f29b345ccb3f4a8fc32c9fac4.json"}}, {"family": "Volders", "given": "Pieter-Jan", "initials": "PJ", "orcid": "0000-0002-2685-2637", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/6fac44563b164dae90052b9764a8f9ab.json"}}, {"family": "Jehmlich", "given": "Nico", "initials": "N", "orcid": "0000-0002-5638-6868", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b1c3e5702c6740c6a4d553b60eee62e3.json"}}, {"family": "Vissers", "given": "Johannes P C", "initials": "JPC", "orcid": "0000-0001-6283-8456", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3cde55fba2234534a8ce709f13478e42.json"}}, {"family": "Wolan", "given": "Dennis W", "initials": "DW", "orcid": "0000-0001-9879-8353", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/635cea76374a4c90a9514aa845b7f59c.json"}}, {"family": "Wang", "given": "Ana Y", "initials": "AY"}, {"family": "Mendoza", "given": "Luis", "initials": "L", "orcid": "0000-0003-0128-8643", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b6e8a7feab0f481eaf6acd7ec097c5c5.json"}}, {"family": "Shofstahl", "given": "Jim", "initials": "J"}, {"family": "Dowsey", "given": "Andrew W", "initials": "AW", "orcid": "0000-0002-7404-9128", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a1cb70e527d84d32b1e995014007efb8.json"}}, {"family": "Griss", "given": "Johannes", "initials": "J", "orcid": "0000-0003-2206-9511", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b001048c5a5148bdb9bd16ff46e067db.json"}}, {"family": "Salek", "given": "Reza M", "initials": "RM", "orcid": "0000-0001-8604-1732", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/62799f5748ef484b816827380b723b2c.json"}}, {"family": "Neumann", "given": "Steffen", "initials": "S", "orcid": "0000-0002-7899-7192", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3fd85c99a6364305ba466010ed3012ec.json"}}, {"family": "Binz", "given": "Pierre-Alain", "initials": "PA", "orcid": "0000-0002-0045-7698", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/f857e16ce82b4242ab0e780c8bec9539.json"}}, {"family": "Lam", "given": "Henry", "initials": "H", "orcid": "0000-0001-7928-0364", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5f27cfbc77fe4122977457e89968814c.json"}}, {"family": "Vizca\u00edno", "given": "Juan Antonio", "initials": "JA", "orcid": "0000-0002-3905-4335", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/81245410f3234e658147bc94f6b3dad2.json"}}, {"family": "Bandeira", "given": "Nuno", "initials": "N"}, {"family": "R\u00f6st", "given": "Hannes", "initials": "H", "orcid": "0000-0003-0990-7488", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/4579af772375404da76c447b23c658a3.json"}}], "type": "journal article", "published": "2018-12-07", "journal": {"title": "J. Proteome Res.", "issn": "1535-3907", "volume": "17", "issue": "12", "pages": "4051-4060", "issn-l": "1535-3893"}, "abstract": "The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion on the current state and future directions of the generation and use of peptide tandem mass spectrometry spectral libraries. Their use in proteomics is growing slowly, but there are multiple challenges in the field that must be addressed to further increase the adoption of spectral libraries and related techniques. The primary bottlenecks are the paucity of high quality and comprehensive libraries and the general difficulty of adopting spectral library searching into existing workflows. There are several existing spectral library formats, but none captures a satisfactory level of metadata; therefore, a logical next improvement is to design a more advanced, Proteomics Standards Initiative-approved spectral library format that can encode all of the desired metadata. The group discussed a series of metadata requirements organized into three designations of completeness or quality, tentatively dubbed bronze, silver, and gold. The metadata can be organized at four different levels of granularity: at the collection (library) level, at the individual entry (peptide ion) level, at the peak (fragment ion) level, and at the peak annotation level. Strategies for encoding mass modifications in a consistent manner and the requirement for encoding high-quality and commonly seen but as-yet-unidentified spectra were discussed. The group also discussed related topics, including strategies for comparing two spectra, techniques for generating representative spectra for a library, approaches for selection of optimal signature ions for targeted workflows, and issues surrounding the merging of two or more libraries into one. We present here a review of this field and the challenges that the community must address in order to accelerate the adoption of spectral libraries in routine analysis of proteomics datasets.", "doi": "10.1021/acs.jproteome.8b00485", "pmid": "30270626", "labels": [], "xrefs": [{"db": "mid", "key": "NIHMS1015163"}, {"db": "pmc", "key": "PMC6443480"}], "notes": [], "created": "2026-08-20T08:12:14.655Z", "modified": "2026-08-20T08:12:15.306Z"}, {"entity": "publication", "iuid": "143a7d8eb97041e0b96883f663e3c04b", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/143a7d8eb97041e0b96883f663e3c04b.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/143a7d8eb97041e0b96883f663e3c04b"}}, "title": "Focus on the spectra that matter by clustering of quantification data in shotgun proteomics", "authors": [{"family": "The", "given": "Matthew", "initials": "M", "orcid": "0000-0002-5401-5553", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9d8d7d850ed24f92b9506b203ca63ed1.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "posted-content", "published": "2018-12-06", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/488015", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T11:11:45.176Z", "modified": "2026-08-20T11:11:45.233Z"}, {"entity": "publication", "iuid": "e274a061192d4e36b8af014c3a3beda8", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/e274a061192d4e36b8af014c3a3beda8.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/e274a061192d4e36b8af014c3a3beda8"}}, "title": "A simple null model for inferences from network enrichment analysis.", "authors": [{"family": "Jeuken", "given": "Gustavo S", "initials": "GS"}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "journal article", "published": "2018-11-09", "journal": {"title": "PLoS ONE", "issn": "1932-6203", "volume": "13", "issue": "11", "pages": "e0206864", "issn-l": "1932-6203"}, "abstract": "A prevailing technique to infer function from lists of identifications, from molecular biological high-throughput experiments, is over-representation analysis, where the identifications are compared to predefined sets of related genes often referred to as pathways. As at least some pathways are known to be incomplete in their annotation, algorithmic efforts have been made to complement them with information from functional association networks. While the terminology varies in the literature, we will here refer to such methods as Network Enrichment Analysis (NEA). Traditionally, the significance of inferences from NEA has been assigned using a null model constructed from randomizations of the network. Here we instead argue for a null model that more directly relates to the set of genes being studied, and have designed one dynamic programming algorithm that calculates the score distribution of NEA scores that makes it possible to assign unbiased mid p values to inferences. We also implemented a random sampling method, carrying out the same task. We demonstrate that our method obtains a superior statistical calibration as compared to the popular NEA inference engine, BinoX, while also providing statistics that are easier to interpret.", "doi": "10.1371/journal.pone.0206864", "pmid": "30412619", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC6226187"}, {"db": "pii", "key": "PONE-D-18-22844"}], "notes": [], "created": "2026-08-20T12:44:02.795Z", "modified": "2026-08-20T12:44:02.826Z"}, {"entity": "publication", "iuid": "f2b02680fd3f4eb3b2572762de32adb2", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/f2b02680fd3f4eb3b2572762de32adb2.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/f2b02680fd3f4eb3b2572762de32adb2"}}, "title": "Quantitative behavior of protein complexes in human cells", "authors": [{"family": "Chalabi", "given": "Morteza H", "initials": "MH", "orcid": "0000-0002-2039-2676", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a81d04ffa5c64ecda6adfc0e0600a3e4.json"}}, {"family": "Tsiamis", "given": "Vasileios", "initials": "V"}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Vandin", "given": "Fabio", "initials": "F", "orcid": "0000-0003-2244-2320", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/75672b522dde4d979568a931eada5c6a.json"}}, {"family": "Schw\u00e4mmle", "given": "Veit", "initials": "V", "orcid": "0000-0002-9708-6722", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/158e08b0cfd34f90882f66142d8e62b7.json"}}], "type": "posted-content", "published": "2018-07-11", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/367227", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T11:10:44.214Z", "modified": "2026-08-20T11:10:44.326Z"}, {"entity": "publication", "iuid": "cc6bf32e36184d888661f18dd3303c43", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/cc6bf32e36184d888661f18dd3303c43.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/cc6bf32e36184d888661f18dd3303c43"}}, "title": "Integrated identification and quantification error probabilities for shotgun proteomics", "authors": [{"family": "The", "given": "Matthew", "initials": "M", "orcid": "0000-0002-5401-5553", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9d8d7d850ed24f92b9506b203ca63ed1.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "posted-content", "published": "2018-06-28", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/357285", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T11:10:34.829Z", "modified": "2026-08-20T11:10:34.853Z"}, {"entity": "publication", "iuid": "bcc3ce0b92d346ef938cd492f9ee633e", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/bcc3ce0b92d346ef938cd492f9ee633e.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/bcc3ce0b92d346ef938cd492f9ee633e"}}, "title": "A protein standard that emulates homology for the characterization of protein inference algorithms", "authors": [{"family": "The", "given": "Matthew", "initials": "M", "orcid": "0000-0002-5401-5553", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9d8d7d850ed24f92b9506b203ca63ed1.json"}}, {"family": "Edfors", "given": "Fredrik", "initials": "F", "orcid": "0000-0002-0017-7987", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9e213b04f8984c8eb00c68f5bc2f6a36.json"}}, {"family": "Perez-Riverol", "given": "Yasset", "initials": "Y", "orcid": "0000-0001-6579-6941", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cb4449bad29741b195a7593fc39a769d.json"}}, {"family": "Payne", "given": "Samuel H", "initials": "SH", "orcid": "0000-0002-8351-1994", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/fe701ec4cf24456980c1902ec61a0ab1.json"}}, {"family": "Hoopmann", "given": "Michael R", "initials": "MR", "orcid": "0000-0001-7029-7792", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/04f75056428f499d9806d2fd85d50e9a.json"}}, {"family": "Palmblad", "given": "Magnus", "initials": "M", "orcid": "0000-0002-5865-8994", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/80053e2256cd4e55afc7ba916821602c.json"}}, {"family": "Forsstr\u00f6m", "given": "Bj\u00f6rn", "initials": "B"}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "posted-content", "published": "2017-12-19", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/236471", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T11:08:00.975Z", "modified": "2026-08-20T11:08:01.125Z"}, {"entity": "publication", "iuid": "b51435ae9ccc4e67baac82324f120ab4", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/b51435ae9ccc4e67baac82324f120ab4.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/b51435ae9ccc4e67baac82324f120ab4"}}, "title": "Covariation of Peptide Abundances Accurately Reflects Protein Concentration Differences.", "authors": [{"family": "Zhang", "given": "Bo", "initials": "B", "orcid": "0000-0001-8890-8416", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/fab1ab9de65a430b97f0a84901798d6e.json"}}, {"family": "Pirmoradian", "given": "Mohammad", "initials": "M"}, {"family": "Zubarev", "given": "Roman", "initials": "R", "orcid": "0000-0001-9839-2089", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5e3f9910c1ff434c8056bdecf537e9ef.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "journal article", "published": "2017-05-00", "journal": {"title": "Mol. Cell Proteomics", "issn": "1535-9484", "volume": "16", "issue": "5", "pages": "936-948", "issn-l": "1535-9476"}, "abstract": "Most implementations of mass spectrometry-based proteomics involve enzymatic digestion of proteins, expanding the analysis to multiple proteolytic peptides for each protein. Currently, there is no consensus of how to summarize peptides' abundances to protein concentrations, and such efforts are complicated by the fact that error control normally is applied to the identification process, and do not directly control errors linking peptide abundance measures to protein concentration. Peptides resulting from suboptimal digestion or being partially modified are not representative of the protein concentration. Without a mechanism to remove such unrepresentative peptides, their abundance adversely impacts the estimation of their protein's concentration. Here, we present a relative quantification approach, Diffacto, that applies factor analysis to extract the covariation of peptides' abundances. The method enables a weighted geometrical average summarization and automatic elimination of incoherent peptides. We demonstrate, based on a set of controlled label-free experiments using standard mixtures of proteins, that the covariation structure extracted by the factor analysis accurately reflects protein concentrations. In the 1% peptide-spectrum match-level FDR data set, as many as 11% of the peptides have abundance differences incoherent with the other peptides attributed to the same protein. If not controlled, such contradicting peptide abundance have a severe impact on protein quantifications. When adding the quantities of each protein's three most abundant peptides, we note as many as 14% of the proteins being estimated as having a negative correlation with their actual concentration differences between samples. Diffacto reduced the amount of such obviously incorrectly quantified proteins to 1.6%. Furthermore, by analyzing clinical data sets from two breast cancer studies, our method revealed the persistent proteomic signatures linked to three subtypes of breast cancer. We conclude that Diffacto can facilitate the interpretation and enhance the utility of most types of proteomics data.", "doi": "10.1074/mcp.O117.067728", "pmid": "28302922", "labels": {"Affiliated researcher": null}, "xrefs": [{"db": "pmc", "key": "PMC5417831"}, {"db": "pii", "key": "S1535-9476(20)32397-5"}], "notes": [], "created": "2018-12-05T12:31:06.349Z", "modified": "2026-08-20T09:32:36.111Z"}, {"entity": "publication", "iuid": "b03ed99bfed54a90a9fe776674ff04c6", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/b03ed99bfed54a90a9fe776674ff04c6.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/b03ed99bfed54a90a9fe776674ff04c6"}}, "title": "DeMix-Q: Quantification-Centered Data Processing Workflow.", "authors": [{"family": "Zhang", "given": "Bo", "initials": "B", "orcid": "0000-0001-8890-8416", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/fab1ab9de65a430b97f0a84901798d6e.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}, {"family": "Zubarev", "given": "Roman A", "initials": "RA", "orcid": "0000-0001-9839-2089", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5e3f9910c1ff434c8056bdecf537e9ef.json"}}], "type": "comparative study", "published": "2016-04-00", "journal": {"title": "Mol. Cell Proteomics", "issn": "1535-9484", "volume": "15", "issue": "4", "pages": "1467-1478", "issn-l": "1535-9476"}, "abstract": "For historical reasons, most proteomics workflows focus on MS/MS identification but consider quantification as the end point of a comparative study. The stochastic data-dependent MS/MS acquisition (DDA) gives low reproducibility of peptide identifications from one run to another, which inevitably results in problems with missing values when quantifying the same peptide across a series of label-free experiments. However, the signal from the molecular ion is almost always present among the MS(1)spectra. Contrary to what is frequently claimed, missing values do not have to be an intrinsic problem of DDA approaches that perform quantification at the MS(1)level. The challenge is to perform sound peptide identity propagation across multiple high-resolution LC-MS/MS experiments, from runs with MS/MS-based identifications to runs where such information is absent. Here, we present a new analytical workflow DeMix-Q (https://github.com/userbz/DeMix-Q), which performs such propagation that recovers missing values reliably by using a novel scoring scheme for quality control. Compared with traditional workflows for DDA as well as previous DIA studies, DeMix-Q achieves deeper proteome coverage, fewer missing values, and lower quantification variance on a benchmark dataset. This quantification-centered workflow also enables flexible and robust proteome characterization based on covariation of peptide abundances.", "doi": "10.1074/mcp.O115.055475", "pmid": "26729709", "labels": {"Affiliated researcher": null}, "xrefs": [{"db": "pmc", "key": "PMC4824868"}, {"db": "pii", "key": "S1535-9476(20)33634-3"}], "notes": [], "created": "2018-12-05T09:57:59.735Z", "modified": "2026-08-20T09:32:30.666Z"}]}