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dc.contributor.authorWheeler, Douglas B.en_US
dc.contributor.authorKang, In Hanen_US
dc.contributor.authorGolland, Polinaen_US
dc.contributor.authorPapallo, Adamen_US
dc.contributor.authorLindquist, Robert A.en_US
dc.contributor.authorJones, Thouis R.en_US
dc.contributor.authorVan Dyk, Anne Carpenteren_US
dc.contributor.authorSabatini, Daviden_US
dc.date.accessioned2009-10-19T13:35:12Z
dc.date.available2009-10-19T13:35:12Z
dc.date.issued2008-11en_US
dc.date.submitted2008-07en_US
dc.identifier.issn1471-2105en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/49464
dc.description.abstractBackground: Image-based screens can produce hundreds of measured features for each of hundreds of millions of individual cells in a single experiment. Results: Here, we describe CellProfiler Analyst, open-source software for the interactive exploration and analysis of multidimensional data, particularly data from high-throughput, image-based experiments. Conclusion: The system enables interactive data exploration for image-based screens and automated scoring of complex phenotypes that require combinations of multiple measured features per cell.en_US
dc.language.isoen_USen_US
dc.publisherBioMed Central Ltd.en_US
dc.relation.isversionofhttp://dx.doi.org/doi:10.1186/1471-2105-9-482en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/2.0en_US
dc.sourcePublisheren_US
dc.titleCellProfiler Analyst: data exploration and analysis software for complex image-based screensen_US
dc.typeArticleen_US
dc.identifier.citationT. Jones, I. Kang, D. Wheeler, R. Lindquist, A. Papallo, D. Sabatini, P. Golland, and A. Carpenter, “CellProfiler Analyst: data exploration and analysis software for complex image-based screens,” BMC Bioinformatics, vol. 9, 2008, p. 482.en_US
dc.contributor.departmentBroad Institute of MIT and Harvarden_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biologyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentWhitehead Institute for Biomedical Researchen_US
dc.contributor.approverSabatini, David M.en_US
dc.contributor.mitauthorJones, Thouis R.en_US
dc.contributor.mitauthorKang, In Hanen_US
dc.contributor.mitauthorWheeler, Douglas B.en_US
dc.contributor.mitauthorPapallo, Adamen_US
dc.contributor.mitauthorLindquist, Robert A.en_US
dc.contributor.mitauthorSabatini, David M.en_US
dc.contributor.mitauthorGolland, Polinaen_US
dc.contributor.mitauthorCarpenter, Anne E.en_US
dc.relation.journalBMC Bioinformaticsen_US
dc.eprint.versionFinal published versionen_US
dc.identifier.pmid19014601en_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsJones, Thouis R; Kang, In; Wheeler, Douglas B; Lindquist, Robert A; Papallo, Adam; Sabatini, David M; Golland, Polina; Carpenter, Anne Een
dc.identifier.orcidhttps://orcid.org/0000-0003-2516-731X
dc.identifier.orcidhttps://orcid.org/0000-0002-1446-7256
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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