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Review of statistical analyses in drug discovery and chemogenomics

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Abstract

A review of the basic organizational structure of chemogenomics outlines how chemoinformatics, combinational and medicinal chemistry integrate with microarray methods and systems biology to discover new drugs. Key statistical issues include investigations of quantitative structural activity relationships (QSARs), the role of compound similarity in constructing experimental designs, and techniques for getting reliable and accurate measures of genomic response. Four current areas of research are highlighted: correlational analyses, integration of non-coding RNA signals into modeling, connectivity maps, and yeast deletion libraries. Copyright © 2009 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 2: 88-102, 2009

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