Linked Life Data

21216932

Source:http://linkedlifedata.com/resource/pubmed/id/21216932

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2011-2-10
pubmed:abstractText
High-content screening is increasingly used to elucidate changes in cellular biology arising from treatment with small molecules and biological probes. We describe a cell classifier for automated analysis of multiparametric data from immunofluorescence microscopy and characterize the phenotypes of 41 cell-cycle modulators, including several protein kinase inhibitors in preclinical and clinical development. This method produces a consistent assessment of treatment-induced phenotypes across experiments done by different biologists and highlights the prevalence of nonuniform and concentration-dependent cellular response to treatment. Contrasting cell phenotypes from high-content screening to kinase selectivity profiles from cell-free assays highlights the limited utility of enzyme potency ratios in understanding the mechanism of action for cell-cycle kinase inhibitors. Our cell-level approach for assessing phenotypic outcomes is reliable, reproducible and capable of supporting medium throughput analyses of a wide range of cellular perturbations.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
1538-8514
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
10
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
242-54
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
A robust high-content imaging approach for probing the mechanism of action and phenotypic outcomes of cell-cycle modulators.
pubmed:affiliation
Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN 46285, USA. sutherlandje@lilly.com
pubmed:publicationType
Journal Article