| Abstract
| - In an effort to enhance access to information available in the National Cancer Institute's (NCI)anticancer drug-screening database, a new suite of Internet accessible (http://spheroid.ncifcrf.gov) computational tools has been assembled for self-organizing map-based (SOM) clusteranalysis and data visualization. A range of analysis questions were initially addressed toevaluate improvements in SOM cluster quality based on the data-conditioning procedures ofZ-score normalization, capping, and treatment of missing data as well as completeness of drugcell-screening data. These studies established a foundation for SOM cluster analysis of thecomplete set of NCI's publicly available antitumor drug-screening data. This analysis identifiedrelationships between chemotypes of screened agents and their effect on four major classes ofcellular activities: mitosis, nucleic acid synthesis, membrane transport and integrity, andphosphatase- and kinase-mediated cell cycle regulation. Validations of these cellular activities,obtained from literature sources, found (i) strong evidence supporting within cluster memberships and shared cellular activity, (ii) indications of compound selectivity between various typesof cellular activity, and (iii) strengths and weaknesses of the NCI's antitumor drug screen datafor assigning compounds to these classes of cellular activity. Subsequent analyses of averagedresponses within these tumor panel types find a strong dependence on chemotype for coherenceamong cellular response patterns. The advantages of a global analysis of the complete screeningdata set are discussed.
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