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CellProfiler: image analysis software for identifying and quantifying cell phenotypes

dc.contributor.authorCarpenter, Anne E.
dc.contributor.authorJones, Thouis R.
dc.contributor.authorLamprecht, Michael R.
dc.contributor.authorClarke, Colin
dc.contributor.authorKang, In Han
dc.contributor.authorFriman, Ola
dc.contributor.authorGuertin, David A.
dc.contributor.authorChang, Joo Han
dc.contributor.authorLindquist, Robert A.
dc.contributor.authorMoffat, Jason
dc.contributor.authorGolland, Polina
dc.contributor.authorSabatini, David
dc.date.accessioned2010-09-29T18:23:23Z
dc.date.available2010-09-29T18:23:23Z
dc.date.issued2006-10
dc.date.submitted2006-09
dc.identifier.issn1465-6906
dc.identifier.urihttp://hdl.handle.net/1721.1/58762
dc.description.abstractBiologists can now prepare and image thousands of samples per day using automation, enabling chemical screens and functional genomics (for example, using RNA interference). Here we describe the first free, open-source system designed for flexible, high-throughput cell image analysis, CellProfiler. CellProfiler can address a variety of biological questions quantitatively, including standard assays (for example, cell count, size, per-cell protein levels) and complex morphological assays (for example, cell/organelle shape or subcellular patterns of DNA or protein staining).en_US
dc.description.sponsorshipMerck/CSBi Fellowshipen_US
dc.description.sponsorshipLife Sciences Research Foundationen_US
dc.description.sponsorshipNovartis Foundationen_US
dc.description.sponsorshipSociety for Biomolecular Screeningen_US
dc.description.sponsorshipMIT EECS/Whitehead/Broad Training Program in Computational Biology (NIH grant DK070069-01)en_US
dc.description.sponsorshipDamon Runyon Cancer Research Foundationen_US
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canadaen_US
dc.description.sponsorshipUnited States. Dept. of Defense (TSC grant W81XWH-05-1-0318-DS)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (NIH grant R01 GM072555-01)en_US
dc.description.sponsorshipW.M. Keck Foundationen_US
dc.publisherBioMed Central Ltden_US
dc.relation.isversionofhttp://dx.doi.org/10.1186/gb-2006-7-10-r100en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/2.0en_US
dc.sourceBioMed Central Ltden_US
dc.titleCellProfiler: image analysis software for identifying and quantifying cell phenotypesen_US
dc.typeArticleen_US
dc.identifier.citationGenome Biology. 2006 Oct 31;7(10):R100en_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.departmentWhitehead Institute for Biomedical Researchen_US
dc.contributor.mitauthorClarke, Colin
dc.contributor.mitauthorGolland, Polina
dc.contributor.mitauthorSabatini, David M.
dc.contributor.mitauthorJones, Thouis R.
dc.contributor.mitauthorKang, In Han
dc.relation.journalGenome biologyen_US
dc.eprint.versionFinal published versionen_US
dc.identifier.pmid17076895
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2010-09-03T16:22:58Z
dc.language.rfc3066en
dc.rights.holderCarpenter et al.; licensee BioMed Central Ltd.
dspace.orderedauthorsCarpenter, Anne E; Jones, Thouis R; Lamprecht, Michael R; Clarke, Colin; Kang, In; Friman, Ola; Guertin, David A; Chang, Joo; Lindquist, Robert A; Moffat, Jason; Golland, Polina; Sabatini, David Men
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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