Identifying genes related to chemosensitivity using support vector machine.

Lei Bao

doi:10.1385/1-59259-889-7:233

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Identifying genes related to chemosensitivity using support vector machine.

Lei Bao

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Abstract

In an effort to identify genes involved in chemosensitivity and to evaluate the functional relationships between genes and anticancer drugs acting by the same mechanism, a supervised machine learning approach called support vector machine (SVM) is used to associate genes with any of five predefined anticancer drug mechanistic categories. The drug activity profiles are used as training examples to train the SVM and then the gene expression profiles are used as test examples to predict their associated mechanistic categories. This method of correlating drugs and genes provides a strategy for finding novel biologically significant relationships for molecular pharmacology.

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Algorithms Antineoplastic Agents Artificial Intelligence Computational Biology DNA DNA Damage DNA Repair Drug Screening Assays, Antitumor Gene Expression Profiling Gene Expression Regulation, Neoplastic Humans Models, Statistical Oligonucleotide Array Sequence Analysis Pattern Recognition, Automated Journal Article

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Lei Bao. 2005. Identifying genes related to chemosensitivity using support vector machine.. https://doi.org/10.1385/1-59259-889-7%3A233

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