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dc.contributor.authorTegner, Jesper
dc.contributor.authorGomez-Cabrero, David
dc.date.accessioned2022-04-17T08:31:19Z
dc.date.available2022-04-17T08:31:19Z
dc.date.issued2022-04-13
dc.identifier.citationTegner, J. N., & Gomez-Cabrero, D. (2022). Data-driven bioinformatics to disentangle cells within a tissue microenvironment. Trends in Cell Biology. https://doi.org/10.1016/j.tcb.2022.03.009
dc.identifier.issn0962-8924
dc.identifier.doi10.1016/j.tcb.2022.03.009
dc.identifier.urihttp://hdl.handle.net/10754/676275
dc.description.abstractMolecular profiling of clinical tissue samples is at the core of precision medicine. Yet, to elucidate the contribution of mixed cell types and detect changes in cell populations in response to infections or drugs is challenging. Recent advances using machine learning promise to learn explanatory models directly from data.
dc.description.sponsorshipJ.N.T and D.G-C acknowledge support from King Abdullah University of Science and Technology.
dc.publisherElsevier BV
dc.relation.urlhttps://linkinghub.elsevier.com/retrieve/pii/S0962892422000812
dc.rightsThis is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectGenomics
dc.subjectBioinformatics
dc.subjectCell type
dc.subjectDeconvolution
dc.subjectPrecision medicine
dc.titleData-driven bioinformatics to disentangle cells within a tissue microenvironment
dc.typeArticle
dc.contributor.departmentBiological and Environmental Science and Engineering (BESE) Division
dc.contributor.departmentBioscience Program
dc.identifier.journalTrends in Cell Biology
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionUnit of Computational Medicine, Department of Medicine, Center for Molecular Medicine, Karolinska Institutet, Karolinska University Hospital, L8:05, SE-171 76, Stockholm, Sweden
dc.contributor.institutionScience for Life Laboratory, Tomtebodavägen 23A, SE-17165, Solna, Sweden
dc.contributor.institutionMucosal and Salivary Biology Division, King's College London Dental Institute, London, UK
dc.contributor.institutionTranslational Bioinformatics Unit, Navarrabiomed, Complejo Hospitalario de Navarra (CHN), Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona, Spain
kaust.personTegner, Jesper
kaust.personGomez-Cabrero, David
refterms.dateFOA2022-04-17T08:32:19Z


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This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Except where otherwise noted, this item's license is described as This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)