Please use this identifier to cite or link to this item:
https://doi.org/10.1177/1087057110372256
DC Field | Value | |
---|---|---|
dc.title | A cell profiling framework for modeling drug responses from HCS imaging | |
dc.contributor.author | Ng, A.Y.J. | |
dc.contributor.author | Rajapakse, J.C. | |
dc.contributor.author | Welsch, R.E. | |
dc.contributor.author | Matsudaira, P.T. | |
dc.contributor.author | Horodincu, V. | |
dc.contributor.author | Evans, J.G. | |
dc.date.accessioned | 2014-10-27T08:18:43Z | |
dc.date.available | 2014-10-27T08:18:43Z | |
dc.date.issued | 2010-08 | |
dc.identifier.citation | Ng, A.Y.J., Rajapakse, J.C., Welsch, R.E., Matsudaira, P.T., Horodincu, V., Evans, J.G. (2010-08). A cell profiling framework for modeling drug responses from HCS imaging. Journal of Biomolecular Screening 15 (7) : 858-868. ScholarBank@NUS Repository. https://doi.org/10.1177/1087057110372256 | |
dc.identifier.issn | 10870571 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/99798 | |
dc.description.abstract | The authors present an unsupervised, scalable, and interpretable cell profiling framework that is compatible with data gathered from high-content screening. They demonstrate the effectiveness of their framework by modeling drug differential effects of IC-21 macrophages treated with microtubule and actin disrupting drugs. They identify significant features of cell phenotypes for unsupervised learning based on maximum relevancy and minimum redundancy criteria. A 2-stage clustering approach annotates, clusters cells, and then merges them together to form super-clusters. An interpretable cell profile consisting of super-cluster proportions profiled at each drug treatment, concentration, or duration is obtained. Differential changes in super-cluster profiles are the basis for understanding the drugs differential effect and biology. The authors method is validated by significant chi-squared statistics obtained from similar drug-treated super-cluster profiles from a 5-fold cross-validation. In addition, drug profiles of 2 microtubule drugs with equivalent mechanisms of action are statistically similar. Several distinct trends are identified for the 5 cytoskeletal drugs profiled under different conditions. © 2010 Society for Laboratory Automation and Screening. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1177/1087057110372256 | |
dc.source | Scopus | |
dc.subject | cell morphology | |
dc.subject | clustering | |
dc.subject | drug profiling | |
dc.subject | high-content screening (HCS) | |
dc.type | Article | |
dc.contributor.department | BIOLOGICAL SCIENCES | |
dc.description.doi | 10.1177/1087057110372256 | |
dc.description.sourcetitle | Journal of Biomolecular Screening | |
dc.description.volume | 15 | |
dc.description.issue | 7 | |
dc.description.page | 858-868 | |
dc.description.coden | JBISF | |
dc.identifier.isiut | 000283799100015 | |
Appears in Collections: | Staff Publications |
Show simple item record
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.