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dc.contributor.authorStrzelecka, Paulina
dc.contributor.authorRanzoni, Anna
dc.contributor.authorCvejic, Ana
dc.date.accessioned2018-12-04T00:30:50Z
dc.date.available2018-12-04T00:30:50Z
dc.date.issued2018-11-05
dc.identifier.issn1754-8403
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/286254
dc.description.abstractProbing cellular population diversity at single-cell resolution became possible only in recent years. The popularity of single-cell 'omic' approaches, which allow researchers to dissect sample heterogeneity and cell-to-cell variation, continues to grow. With continuous technological improvements, single-cell omics are becoming increasingly prevalent and contribute to the discovery of new and rare cell types, and to the deciphering of disease pathogenesis and outcome. Animal models of human diseases have significantly facilitated our understanding of the mechanisms driving pathologies and resulted in the development of more efficient therapies. The application of single-cell omics to animal models improves the precision of the obtained insights, and brings single-cell technology closer to the clinical field. This Review focuses on the use of single-cell omics in cellular and animal models of diseases, as well as in samples from human patients. It also highlights the potential of these approaches to further improve the diagnosis and treatment of various pathologies, and includes a discussion of the advantages and remaining challenges in implementing these technologies into clinical practice.
dc.description.sponsorshipThe study was supported by Cancer Research UK grant number C45041/A14953 and European Research Council project 677501 – ZF_Blood. The authors would like to thank Jana Elias for generating Figure 1.
dc.format.mediumElectronic
dc.languageeng
dc.publisherThe Company of Biologists
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectHumans
dc.subjectDisease
dc.subjectProteomics
dc.subjectGenomics
dc.subjectModels, Biological
dc.subjectMetabolomics
dc.subjectSingle-Cell Analysis
dc.titleDissecting human disease with single-cell omics: application in model systems and in the clinic.
dc.typeArticle
prism.issueIdentifier11
prism.publicationDate2018
prism.publicationNameDis Model Mech
prism.volume11
dc.identifier.doi10.17863/CAM.33566
dcterms.dateAccepted2018-09-19
rioxxterms.versionofrecord10.1242/dmm.036525
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2018-11-05
dc.contributor.orcidStrzelecka, Paulina [0000-0003-0226-6788]
dc.contributor.orcidRanzoni, Anna [0000-0002-2573-1382]
dc.contributor.orcidCvejic, Ana [0000-0003-3204-9311]
dc.identifier.eissn1754-8411
rioxxterms.typeJournal Article/Review
pubs.funder-project-idCancer Research Uk (None)
pubs.funder-project-idMedical Research Council (MC_PC_12009)
pubs.funder-project-idEuropean Research Council (677501)
cam.issuedOnline2018-11-05


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International