{"entity": "researcher", "timestamp": "2026-08-20T21:35:38.600Z", "family": "Theis", "given": "Fabian J", "initials": "FJ", "orcid": "0000-0002-2419-1943", "affiliations": ["Institute of Computational Biology, Helmholtz Zentrum M\u00fcnchen, Neuherberg, Germany."], "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/researcher/8969d033a36f40aab191ad1b3960114d.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/researcher/8969d033a36f40aab191ad1b3960114d"}}, "publications": [{"entity": "publication", "iuid": "e7049b1e01f1419e9f26134ae55daedd", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/e7049b1e01f1419e9f26134ae55daedd.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/e7049b1e01f1419e9f26134ae55daedd"}}, "title": "Probe set selection for targeted spatial transcriptomics.", "authors": [{"family": "Kuemmerle", "given": "Louis B", "initials": "LB", "orcid": "0000-0002-9193-1243", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/31e2ab0bc76a4fb1bf1cf184b487c222.json"}}, {"family": "Luecken", "given": "Malte D", "initials": "MD", "orcid": "0000-0001-7464-7921", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/573854d96a9e4e21a3b96135c11c6efc.json"}}, {"family": "Firsova", "given": "Alexandra B", "initials": "AB"}, {"family": "Barros de Andrade E Sousa", "given": "Lisa", "initials": "L"}, {"family": "Stra\u00dfer", "given": "Lena", "initials": "L"}, {"family": "Mekki", "given": "Ilhem Isra", "initials": "II"}, {"family": "Campi", "given": "Francesco", "initials": "F"}, {"family": "Heumos", "given": "Lukas", "initials": "L"}, {"family": "Shulman", "given": "Maiia", "initials": "M", "orcid": "0009-0006-6308-1997", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/f4bef2f0f2514292b767f2fafd6fed60.json"}}, {"family": "Beliaeva", "given": "Valentina", "initials": "V"}, {"family": "Hediyeh-Zadeh", "given": "Soroor", "initials": "S", "orcid": "0000-0001-7513-6779", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5a9996c51c9d43c6a40db9c46d213399.json"}}, {"family": "Schaar", "given": "Anna C", "initials": "AC"}, {"family": "Mahbubani", "given": "Krishnaa T", "initials": "KT", "orcid": "0000-0002-1327-2334", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/de56aac2975a4292b9e6d1eeb8b74d02.json"}}, {"family": "Sountoulidis", "given": "Alexandros", "initials": "A", "orcid": "0000-0002-8837-4642", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/618bb4684ceb4d839a2a83d4a7bca479.json"}}, {"family": "Balassa", "given": "Tam\u00e1s", "initials": "T"}, {"family": "Kovacs", "given": "Ferenc", "initials": "F", "orcid": "0000-0003-4512-4448", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/15d35f638dcc4014afbc2a3ef5e22418.json"}}, {"family": "Horvath", "given": "Peter", "initials": "P"}, {"family": "Piraud", "given": "Marie", "initials": "M"}, {"family": "Ert\u00fcrk", "given": "Ali", "initials": "A", "orcid": "0000-0001-5163-5100", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/dc5ed46442424675b629587c6ac826d5.json"}}, {"family": "Samakovlis", "given": "Christos", "initials": "C"}, {"family": "Theis", "given": "Fabian J", "initials": "FJ", "orcid": "0000-0002-2419-1943", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8969d033a36f40aab191ad1b3960114d.json"}}], "type": "journal article", "published": "2024-12-00", "journal": {"title": "Nat. Methods", "issn": "1548-7105", "volume": "21", "issue": "12", "pages": "2260-2270", "issn-l": "1548-7091"}, "abstract": "Targeted spatial transcriptomic methods capture the topology of cell types and states in tissues at single-cell and subcellular resolution by measuring the expression of a predefined set of genes. The selection of an optimal set of probed genes is crucial for capturing the spatial signals present in a tissue. This requires selecting the most informative, yet minimal, set of genes to profile (gene set selection) for which it is possible to build probes (probe design). However, current selections often rely on marker genes, precluding them from detecting continuous spatial signals or new states. We present Spapros, an end-to-end probe set selection pipeline that optimizes both gene set specificity for cell type identification and within-cell type expression variation to resolve spatially distinct populations while considering prior knowledge as well as probe design and expression constraints. We evaluated Spapros and show that it outperforms other selection approaches in both cell type recovery and recovering expression variation beyond cell types. Furthermore, we used Spapros to design a single-cell resolution in situ hybridization on tissues (SCRINSHOT) experiment of adult lung tissue to demonstrate how probes selected with Spapros identify cell types of interest and detect spatial variation even within cell types.", "doi": "10.1038/s41592-024-02496-z", "pmid": "39558096", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC11621025"}, {"db": "pii", "key": "10.1038/s41592-024-02496-z"}], "notes": [], "created": "2026-08-20T09:03:14.919Z", "modified": "2026-08-20T09:03:15.285Z"}, {"entity": "publication", "iuid": "5fc47a4102964480960ca7e6f1d5a6d4", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/5fc47a4102964480960ca7e6f1d5a6d4.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/5fc47a4102964480960ca7e6f1d5a6d4"}}, "title": "OME-Zarr: a cloud-optimized bioimaging file format with international community support.", "authors": [{"family": "Moore", "given": 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"2023-09-00", "journal": {"title": "Histochem Cell Biol", "issn": "1432-119X", "volume": "160", "issue": "3", "pages": "223-251", "issn-l": null}, "abstract": "A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself-OME-Zarr-along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain-the file format that underlies so many personal, institutional, and global data management and analysis tasks.", "doi": "10.1007/s00418-023-02209-1", "pmid": "37428210", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC10492740"}, {"db": "pii", "key": "10.1007/s00418-023-02209-1"}], "notes": [], "created": "2026-08-20T06:39:48.671Z", "modified": "2026-08-20T06:39:51.326Z"}, {"entity": "publication", "iuid": "1c7447d86c504d7abceb68914defaf42", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/1c7447d86c504d7abceb68914defaf42.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/1c7447d86c504d7abceb68914defaf42"}}, "title": "OME-Zarr: a cloud-optimized bioimaging file format with international community support.", "authors": [{"family": "Moore", "given": "Josh", "initials": "J", "orcid": "0000-0003-4028-811X", "researcher": 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"2023-05-07", "journal": {"title": "bioRxiv", "issn": "2692-8205", "issn-l": null}, "abstract": "A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself -- OME-Zarr -- along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. 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"Theis", "given": "Fabian J", "initials": "FJ", "orcid": "0000-0002-2419-1943", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8969d033a36f40aab191ad1b3960114d.json"}}, {"family": "Torres-Padilla", "given": "Maria-Elena", "initials": "ME", "orcid": "0000-0002-1020-2074", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/eff16da68dab4d46824ef56f3285de75.json"}}, {"family": "Valencia", "given": "Alfonso", "initials": "A"}, {"family": "Vallot", "given": "C\u00e9line", "initials": "C", "orcid": "0000-0003-1601-2359", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3094c4eff5fd46349912630f1770636a.json"}}, {"family": "van Oudenaarden", "given": "Alexander", "initials": "A", "orcid": "0000-0002-9442-3551", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/33649d3f227046eea9f3b3ce835d9057.json"}}, {"family": "Vidal", "given": "Marie", "initials": "M", "orcid": "0000-0003-1186-9994", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/077f341fdc4441d681ee1ecbd8edd039.json"}}, {"family": "Voet", "given": "Thierry", "initials": "T"}, {"family": "LifeTime Community Working Groups", "given": "", "initials": ""}], "type": "journal article", "published": "2020-11-00", "journal": {"title": "Nature", "issn": "1476-4687", "volume": "587", "issue": "7834", "pages": "377-386", "issn-l": "0028-0836"}, "abstract": "Here we describe the LifeTime Initiative, which aims to track, understand and target human cells during the onset and progression of complex diseases, and to analyse their response to therapy at single-cell resolution. This mission will be implemented through the development, integration and application of single-cell multi-omics and imaging, artificial intelligence and patient-derived experimental disease models during the progression from health to disease. The analysis of large molecular and clinical datasets will identify molecular mechanisms, create predictive computational models of disease progression, and reveal new drug targets and therapies. The timely detection and interception of disease embedded in an ethical and patient-centred vision will be achieved through interactions across academia, hospitals, patient associations, health data management systems and industry. The application of this strategy to key medical challenges in cancer, neurological and neuropsychiatric disorders, and infectious, chronic inflammatory and cardiovascular diseases at the single-cell level will usher in cell-based interceptive medicine in Europe over the next decade.", "doi": "10.1038/s41586-020-2715-9", "pmid": "32894860", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC7656507"}, {"db": "pii", "key": "10.1038/s41586-020-2715-9"}], "notes": [], "created": "2026-08-20T08:56:17.301Z", "modified": "2026-08-20T08:56:55.192Z"}]}