Swinney, D.C. & Anthony, J. How were new medicines discovered? Nat. Rev. Drug Discov. 10, 507–519 (2011).
Swinney, D.C. The contribution of mechanistic understanding to phenotypic screening for first-in-class medicines. J. Biomol. Screen. 18, 1186–1192 (2013).
Moffat, J.G., Joachim, R. & David, B. Phenotypic screening in cancer drug discovery — past, present and future. Nat. Rev. Drug Discov. 13, 588–602 (2014).
Johannessen, C.M., Clemons, P.A. & Wagner, B.K. Integrating phenotypic small-molecule profiling and human genetics: the next phase in drug discovery. Trends Genet. 31, 16–23 (2015).
Bickle, M. The beautiful cell: high-content screening in drug discovery. Anal. Bioanal. Chem. 398, 219–226 (2010).
Singh, S., Carpenter, A.E. & Genovesio, A. Increasing the content of high-content screening: an overview. J. Biomol. Screen. 19, 640–650 (2014).
Perlman, Z.E. et al. Multidimensional drug profiling by automated microscopy. Science 306, 1194–1198 (2004).
Danuser, G. Computer vision in cell biology. Cell 147, 973–978 (2011).
Altschuler, S.J. & Wu, L.F. Cellular heterogeneity: do differences make a difference? Cell 141, 559–563 (2010).
Snijder, B. & Pelkmans, L. Origins of regulated cell-to-cell variability. Nat. Rev. Mol. Cell Biol. 12, 119–125 (2011).
Eliceiri, K.W. et al. Biological imaging software tools. Nat. Methods 9, 697–710 (2012).
Paull, K.D. et al. Display and analysis of patterns of differential activity of drugs against human tumor cell lines: development of mean graph and COMPARE algorithm. J. Natl. Cancer Inst. 81, 1088–1092 (1989).
Lamb, J. et al. The connectivity map: using gene-expression signatures to connect small molecules, genes, and disease. Science 313, 1929–1935 (2006).
Adams, C.L. et al. Compound classification using image-based cellular phenotypes. Methods Enzymol. 414, 440–468 (2006).
Loo, L.-H., Wu, L.F. & Altschuler, S.J. Image-based multivariate profiling of drug responses from single cells. Nat. Methods 4, 445–453 (2007).
Young, D.W. et al. Integrating high-content screening and ligand-target prediction to identify mechanism of action. Nat. Chem. Biol. 4, 59–68 (2008).
Ljosa, V. et al. Comparison of methods for image-based profiling of cellular morphological responses to small-molecule treatment. J. Biomol. Screen. 18, 1321–1329 (2013).
Reisen, F. et al. Linking phenotypes and modes of action through high-content screen fingerprints. Assay Drug Dev. Technol. 13, 415–427 (2015).
Futamura, Y. et al. Morphobase, an encyclopedic cell morphology database, and its use for drug target identification. Chem. Biol. 19, 1620–1630 (2012).
Sundaramurthy, V. et al. Integration of chemical and RNAi multiparametric profiles identifies triggers of intracellular mycobacterial killing. Cell Host Microbe 13, 129–142 (2013).
Castoreno, A.B. et al. Small molecules discovered in a pathway screen target the Rho pathway in cytokinesis. Nat. Chem. Biol. 6, 457–463 (2010).
Loo, L.-H. et al. An approach for extensibly profiling the molecular states of cellular subpopulations. Nat. Methods 6, 759–765 (2009).
Fuchs, F. et al. Clustering phenotype populations by genome-wide RNAi and multiparametric imaging. Mol. Syst. Biol. 6, 370 (2010).
Collinet, C. et al. Systems survey of endocytosis by multiparametric image analysis. Nature 464, 243–249 (2010).
Laufer, C., Fischer, B., Billmann, M., Huber, W. & Boutros, M. Mapping genetic interactions in human cancer cells with RNAi and multiparametric phenotyping. Nat. Methods 10, 427–431 (2013).
Liberali, P., Snijder, B. & Pelkmans, L. A hierarchical map of regulatory genetic interactions in membrane trafficking. Cell 157, 1473–1487 (2014).
Fischer, B. et al. A map of directional genetic interactions in a metazoan cell. Elife 4, e05464 (2015).
Yin, Z. et al. A screen for morphological complexity identifies regulators of switch-like transitions between discrete cell shapes. Nat. Cell Biol. 15, 860–871 (2013).
Gustafsdottir, S.M. et al. Multiplex cytological profiling assay to measure diverse cellular states. PLoS One 8, e80999 (2013).
Wawer, M.J. et al. Toward performance-diverse small-molecule libraries for cell-based phenotypic screening using multiplexed high-dimensional profiling. Proc. Natl. Acad. Sci. USA 111, 10911–10916 (2014).
Singh, S. et al. Morphological profiles of RNAi-induced gene knockdown are highly reproducible but dominated by seed effects. PLoS One 10, e0131370 (2015).
Gibson, C.C. et al. Strategy for identifying repurposed drugs for the treatment of cerebral cavernous malformation. Circulation 131, 289–299 (2015).
MacRae, C.A. A new phenotypic lexicon for accelerated translation: rise of the machines. Circulation 131, 234–236 (2015).
Petrone, P.M. et al. Biodiversity of small molecules--a new perspective in screening set selection. Drug Discov. Today 18, 674–680 (2013).
Peck, D. et al. A method for high-throughput gene expression signature analysis. Genome Biol. 7, R61 (2006).
Rajaram, S., Pavie, B., Wu, L.F. & Altschuler, S.J. PhenoRipper: software for rapidly profiling microscopy images. Nat. Methods 9, 635–637 (2012).
Hartwell, K.A. et al. Niche-based screening identifies small-molecule inhibitors of leukemia stem cells. Nat. Chem. Biol. 9, 840–848 (2013).
Uhlmann, V., Singh, S. & Carpenter, A.E. CP-CHARM: segmentation-free image classification made accessible. BMC Bioinformatics 17, 51 (2016).
Bray, M.-A. & Carpenter, A. in Assay Guidance Manual (eds. Sittampalam, G.S. et al.) (Eli Lilly & Company and the National Center for Advancing Translational Sciences, 2013).
Iversen, P.W. et al. in Assay Guidance Manual (eds. Sittampalam, G.S. et al.) (Eli Lilly & Company and the National Center for Advancing Translational Sciences, 2012).
Singh, S., Bray, M.-A., Jones, T.R. & Carpenter, A.E. Pipeline for illumination correction of images for high-throughput microscopy. J. Microsc. 256, 231–236 (2014).
Bray, M.-A., Fraser, A.N., Hasaka, T.P. & Carpenter, A.E. Workflow and metrics for image quality control in large-scale high-content screens. J. Biomol. Screen. 17, 266–274 (2012).
Clarke, R. et al. The properties of high-dimensional data spaces: implications for exploring gene and protein expression data. Nat. Rev. Cancer 8, 37–49 (2008).
Feng, Y., Mitchison, T.J., Bender, A., Young, D.W. & Tallarico, J.A. Multi-parameter phenotypic profiling: using cellular effects to characterize small-molecule compounds. Nat. Rev. Drug Discov. 8, 567–578 (2009).
Janzen, W.P. & Popa-Burke, I.G. Advances in improving the quality and flexibility of compound management. J. Biomol. Screen. 14, 444–451 (2009).
Lundholt, B.K., Scudder, K.M. & Pagliaro, L. A simple technique for reducing edge effect in cell-based assays. J. Biomol. Screen. 8, 566–570 (2003).
Ljosa, V., Sokolnicki, K.L. & Carpenter, A.E. Annotated high-throughput microscopy image sets for validation. Nat. Methods 9, 637 (2012).
Guyon, I. & Elisseeff, A. An introduction to variable and feature selection. J. Mach. Learn. Res. 3, 1157–1182 (2003).
Carpenter, A.E. et al. CellProfiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biol. 7, R100 (2006).