Developers
Jungseog Kang,
Description of the technology
This technology is a version of
The technology provides a method for systematically identifying optimal reporter cell lines for annotating compound libraries (ORACLs), whose phenotypic profiles most accurately classify a training set of known drugs. This method is realized in three steps. First, a library of
The technology showed its applicability in the process of validation with use of various compounds. The high overall validation rate of 85% demonstrates that this approach can produce high quality compound «leads» across diverse drug classes.
Practical application
The technology can be applicable and highly useful for drug discovery. Main instrument of this technology − optimal reporter cell lines for annotating compound libraries (ORACL) − can functionally annotate large compound libraries across diverse drug classes in a
Laboratories
- Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas (USA)
- Department of Arts and Science, New York
University-Shanghai , Shanghai (China) - Simmons Cancer Center, University of Texas Southwestern Medical Center, Dallas (USA)
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco (USA)
Links
http://www.nature.com/nbt/journal/v34/n1/full/nbt.3419.htmlPublications
- Kang, J. et al. «Improving drug discovery with
high-content phenotypic screens by - Loo, L.H., Wu, L.F., Altschuler, S.J. «
Image-based multivariate profiling of drug responses from single cells." 4.5 Nat Methods. (2007): 445−453. - Rajaram, S. et al. «PhenoRipper: software for rapidly profiling microscopy images." 9.7 Nat Methods. (2012): 635−637