Issues in omics data integration for gene set analysis and aberrant pathway identification

Michael F. Ochs

doi:10.1002/ddr.21046

Issues in omics data integration for gene set analysis and aberrant pathway identification

Michael F. Ochs

School of Medicine

Research output: Contribution to journal › Article › peer-review

Abstract

The impact of omics technologies, from microarrays to next-generation sequencing, on drug development has been limited by our inability to integrate the data meaningfully for pathway analysis. Here we discuss the relationship between biomolecules and pathway activity, focusing on metabolic and signaling pathways. We discuss how each type of pathway requires a different approach to the generation of pathway statistics from omics data and provide guidance for the creation of appropriate gene sets for pathway analysis.

Original language	English (US)
Pages (from-to)	528-534
Number of pages	7
Journal	Drug Development Research
Volume	73
Issue number	8
DOIs	https://doi.org/10.1002/ddr.21046
State	Published - Dec 2012

Keywords

biostatistics
cell signaling
gene set analysis
metabolic pathway
microarray

ASJC Scopus subject areas

Drug Discovery

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10.1002/ddr.21046

Cite this

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Issues in omics data integration for gene set analysis and aberrant pathway identification

Abstract

Keywords

ASJC Scopus subject areas

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