Drug-pathway association analysis: Integration of high-dimensional transcriptional and drug sensitivity profile

Cong Li, Can Yang, Greg Hather, Ray Liu, Hongyu Zhao

Research output: Chapter in book/report/conference proceedingChapterpeer-review

Abstract

Traditional drug discovery practices usually adopt the "one drug - one target" approach, which ignore the fact the disease occurrence is usually the result of an extremely complex combination of molecular events. Pathway-based approaches address this limitation by considering biological pathways as potential drug targets. A first step of pathwaybased drug discovery is to identify associations between drug candidates and biological pathways. This has been made possible by the availability of high-dimensional transcriptional and drug sensitivity profile data. In this chapter, we describe two statistical methods, "iFad" and "iPad", which perform drug-pathway association analysis by integrating these two types high-dimensional data. We also demonstrate their utilities by applying them to the NCI-60 data set.

Original languageEnglish
Title of host publicationIntegrating Omics Data
PublisherCambridge University Press
Pages425-444
Number of pages20
ISBN (Electronic)9781107706484
ISBN (Print)9781107069114
DOIs
Publication statusPublished - 1 Jan 2015

Scopus Subject Areas

  • General Medicine

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