A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia

A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia

Identification of markers of drug response is essential for precision therapy. Here the authors introduce an algorithm that uses prior information about each gene’s importance in AML to identify the most predictive gene-drug associations from transcriptome and drug response data from 30 AML samples....

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Auteurs principaux: Su-In Lee, Safiye Celik, Benjamin A. Logsdon, Scott M. Lundberg, Timothy J. Martins, Vivian G. Oehler, Elihu H. Estey, Chris P. Miller, Sylvia Chien, Jin Dai, Akanksha Saxena, C. Anthony Blau, Pamela S. Becker
Format: article
Langue:EN
Publié: Nature Portfolio 2018
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Accès en ligne:https://doaj.org/article/ff277a1927e34d3491a2ec37c88816b8
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Résumé:Identification of markers of drug response is essential for precision therapy. Here the authors introduce an algorithm that uses prior information about each gene’s importance in AML to identify the most predictive gene-drug associations from transcriptome and drug response data from 30 AML samples.

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