Network biology methods integrating biological data for translational science

Gurkan Bebek, Mehmet Koyutürk, Nathan D. Price, Mark R. Chance

Research output: Contribution to journalArticlepeer-review

Abstract

The explosion of biomedical data, both on the genomic and proteomic side as well as clinical data, will require complex integration and analysis to provide new molecular variables to better understand the molecular basis of phenotype. Currently, much data exist in silos and is not analyzed in frameworks where all data are brought to bear in the development of biomarkers and novel functional targets. This is beginning to change. Network biology approaches, which emphasize the interactions between genes, proteins and metabolites provide a framework for data integration such that genome, proteome, metabolome and other -omics data can be jointly analyzed to understand and predict disease phenotypes. In this review, recent advances in network biology approaches and results are identified. A common theme is the potential for network analysis to provide multiplexed and functionally connected biomarkers for analyzing the molecular basis of disease, thus changing our approaches to analyzing and modeling genome- and proteome-wide data.

Original languageEnglish (US)
Article numberbbr075
Pages (from-to)446-459
Number of pages14
JournalBriefings in bioinformatics
Volume13
Issue number4
DOIs
StatePublished - Jul 2012
Externally publishedYes

Keywords

  • Bioinformatics
  • Network biology

ASJC Scopus subject areas

  • Information Systems
  • Molecular Biology

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