{"entity": "researcher", "timestamp": "2026-08-20T21:26:33.325Z", "family": "Emanuelsson", "given": "Olof", "initials": "O", "orcid": "0000-0002-8879-9245", "affiliations": ["Science for Life Laboratory, Department of Gene Technology, School of Engineering Sciences in Biotechnology, Chemistry and Health, KTH Royal Institute of Technology, Stockholm SE-100 44, Sweden."], "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/researcher/a51c22f2bc594fe3a349bec5363f394f.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/researcher/a51c22f2bc594fe3a349bec5363f394f"}}, "publications": [{"entity": "publication", "iuid": "600b671e0d0e4a429f71129692083fca", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/600b671e0d0e4a429f71129692083fca.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/600b671e0d0e4a429f71129692083fca"}}, "title": "Zfp697 is an RNA-binding protein that regulates skeletal muscle inflammation and remodeling.", "authors": [{"family": "Correia", "given": "Jorge C", "initials": "JC"}, {"family": "Jannig", "given": "Paulo R", "initials": "PR"}, {"family": "Gosztyla", "given": "Maya L", "initials": "ML"}, {"family": "Cervenka", "given": "Igor", "initials": "I"}, {"family": "Ducommun", "given": "Serge", "initials": "S", "orcid": "0000-0002-9230-8867", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5c1b9a8754a94247890161403bbffb6b.json"}}, {"family": "Pr\u00e6stholm", "given": "Stine M", "initials": "SM"}, {"family": "Dias", "given": "Jos\u00e9 M", "initials": "JM", "orcid": "0000-0002-1402-0323", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/baa189d497af4380b7db4c1aba55ae80.json"}}, {"family": "Dumont", "given": "Kyle D", "initials": "KD", "orcid": "0009-0009-4480-301X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/7d3a06df3e1641d6b3fe0ef1875eb92a.json"}}, {"family": "Liu", "given": "Zhengye", "initials": "Z"}, {"family": "Liang", "given": "Qishan", "initials": "Q"}, {"family": "Edsg\u00e4rd", "given": "Daniel", "initials": "D"}, {"family": "Emanuelsson", "given": "Olof", "initials": "O", "orcid": "0000-0002-8879-9245", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a51c22f2bc594fe3a349bec5363f394f.json"}}, {"family": "Gregorevic", "given": "Paul", "initials": "P", "orcid": "0000-0002-7418-8945", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/62ddff2eba364838a40f5f80b00bc5c2.json"}}, {"family": "Westerblad", "given": "H\u00e5kan", "initials": "H", "orcid": "0000-0002-8180-3029", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/88786108b3c14cf18370062b97c20968.json"}}, {"family": "Venckunas", "given": "Tomas", "initials": "T"}, {"family": "Brazaitis", "given": "Marius", "initials": "M"}, {"family": "Kamandulis", "given": "Sigitas", "initials": "S", "orcid": "0000-0001-6476-1069", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9ba086f850e646fb8c962bf4151f82ed.json"}}, {"family": "Lanner", "given": "Johanna T", "initials": "JT", "orcid": "0000-0002-1222-9473", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cfcba9c7fd564b96bd6e2c6ca59d42c7.json"}}, {"family": "Teixeira", "given": "Ana I", "initials": "AI"}, {"family": "Yeo", "given": "Gene W", "initials": "GW"}, {"family": "Ruas", "given": "Jorge L", "initials": "JL", "orcid": "0000-0002-1110-2606", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/73de4393ec8a473e9ae7b23dd090054e.json"}}], "type": "journal article", "published": "2024-08-20", "journal": {"title": "Proc. Natl. Acad. Sci. U.S.A.", "issn": "1091-6490", "volume": "121", "issue": "34", "pages": "e2319724121", "issn-l": "0027-8424"}, "abstract": "Skeletal muscle atrophy is a morbidity and mortality risk factor that happens with disuse, chronic disease, and aging. The tissue remodeling that happens during recovery from atrophy or injury involves changes in different cell types such as muscle fibers, and satellite and immune cells. Here, we show that the previously uncharacterized gene and protein Zfp697 is a damage-induced regulator of muscle remodeling. Zfp697/ZNF697 expression is transiently elevated during recovery from muscle atrophy or injury in mice and humans. Sustained Zfp697 expression in mouse muscle leads to a gene expression signature of chemokine secretion, immune cell recruitment, and extracellular matrix remodeling. Notably, although Zfp697 is expressed in several cell types in skeletal muscle, myofiber-specific Zfp697 genetic ablation in mice is sufficient to hinder the inflammatory and regenerative response to muscle injury, compromising functional recovery. We show that Zfp697 is an essential mediator of the interferon gamma response in muscle cells and that it functions primarily as an RNA-interacting protein, with a very high number of miRNA targets. This work identifies Zfp697 as an integrator of cell-cell communication necessary for tissue remodeling and regeneration.", "doi": "10.1073/pnas.2319724121", "pmid": "39141348", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC11348326"}], "notes": [], "created": "2026-08-20T09:31:32.478Z", "modified": "2026-08-20T09:31:32.827Z"}, {"entity": "publication", "iuid": "1747f563e3d0432b8c0965b609614d6b", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/1747f563e3d0432b8c0965b609614d6b.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/1747f563e3d0432b8c0965b609614d6b"}}, "title": "Detecting sequence signals in targeting peptides using deep learning.", "authors": [{"family": "Almagro Armenteros", "given": "Jose Juan", "initials": "JJ"}, {"family": "Salvatore", "given": "Marco", "initials": "M", "orcid": "0000-0001-5775-0417", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/cc13d7ecab9d4dc6b5330f387678a699.json"}}, {"family": "Emanuelsson", "given": "Olof", "initials": "O", "orcid": "0000-0002-8879-9245", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a51c22f2bc594fe3a349bec5363f394f.json"}}, {"family": "Winther", "given": "Ole", "initials": "O"}, {"family": "von Heijne", "given": "Gunnar", "initials": "G", "orcid": "0000-0002-4490-8569", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/529a460e668a479ca7d9b9271375ef9f.json"}}, {"family": "Elofsson", "given": "Arne", "initials": "A", "orcid": "0000-0002-7115-9751", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/248e70e81bd64f31a5f83e6e329bba95.json"}}, {"family": "Nielsen", "given": "Henrik", "initials": "H", "orcid": "0000-0002-9412-9643", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/95aab73521844700a8137cfc2cb287b0.json"}}], "type": "journal article", "published": "2019-10-00", "journal": {"title": "Life Sci. Alliance", "issn": "2575-1077", "volume": "2", "issue": "5", "issn-l": null}, "abstract": "In bioinformatics, machine learning methods have been used to predict features embedded in the sequences. In contrast to what is generally assumed, machine learning approaches can also provide new insights into the underlying biology. Here, we demonstrate this by presenting TargetP 2.0, a novel state-of-the-art method to identify N-terminal sorting signals, which direct proteins to the secretory pathway, mitochondria, and chloroplasts or other plastids. By examining the strongest signals from the attention layer in the network, we find that the second residue in the protein, that is, the one following the initial methionine, has a strong influence on the classification. We observe that two-thirds of chloroplast and thylakoid transit peptides have an alanine in position 2, compared with 20% in other plant proteins. We also note that in fungi and single-celled eukaryotes, less than 30% of the targeting peptides have an amino acid that allows the removal of the N-terminal methionine compared with 60% for the proteins without targeting peptide. The importance of this feature for predictions has not been highlighted before.", "doi": "10.26508/lsa.201900429", "pmid": "31570514", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC6769257"}, {"db": "pii", "key": "2/5/e201900429"}], "notes": [], "created": "2026-08-20T13:03:51.409Z", "modified": "2026-08-20T13:03:51.559Z"}, {"entity": "publication", "iuid": "840683b953bf44e1ae623f117e0ebbcd", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/840683b953bf44e1ae623f117e0ebbcd.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/840683b953bf44e1ae623f117e0ebbcd"}}, "title": "Detecting Novel Sequence Signals in Targeting Peptides Using Deep Learning", "authors": [{"family": "Almagro Armenteros", "given": "J J", "initials": "JJ"}, {"family": "Salvatore", "given": "M", "initials": "M"}, {"family": "Emanuelsson", "given": "O", "initials": "O", "orcid": "0000-0002-8879-9245", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a51c22f2bc594fe3a349bec5363f394f.json"}}, {"family": "Winther", "given": "O", "initials": "O"}, {"family": "von Heijne", "given": "G", "initials": "G", "orcid": "0000-0002-4490-8569", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/529a460e668a479ca7d9b9271375ef9f.json"}}, {"family": "Elofsson", "given": "A", "initials": "A", "orcid": "0000-0002-7115-9751", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/248e70e81bd64f31a5f83e6e329bba95.json"}}, {"family": "Nielsen", "given": "H", "initials": "H"}], "type": "posted-content", "published": "2019-05-17", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/639203", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T11:13:47.748Z", "modified": "2026-08-20T11:13:47.788Z"}]}