Molecular signatures drive the understanding and treatment of cancer

Jill Mesirov
University of California, San Diego (UCSD)
Center for Genome Research

Machine learning techniques are now vital for the analysis of the explosion of biological data resulting from the advent of new technology developed during and since the Human Genome Project. We will describe the methods and their application to the challenge of integrating different types of genomic data to determine tumor subtypes, patient diagnosis and stratification, and the identification of compounds for treatment.

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