Integrative System Biology Strategies for Disease Biomarker Discovery

Title: Integrative System Biology Strategies for Disease Biomarker Discovery

Volume: 15 Issue: 4

Author(s): Haiyuan Zhang, Hao Hu, Cao Deng, Yeona Chun, Shengtao Zhou, Fuqiang Huang and Qin Zhou

Affiliation:

Keywords: Disease biomarkers, high-throughput, integrative system biology, diagnose, drug, post-genomics, mRNA, cDNA, SAGE, mass spectrometry, nuclear magnetic resonance, bioinformatics, pathologic cells, biochemical pathways, metabolic analysis, genes, probes

Abstract: Biomarkers are currently widely used to diagnose diseases, monitor treatments, and evaluate potential drug candidates. Research of differential Omics accelerate the advancements of biomarkers discovery. By extracting biological knowledge from the ‘omics’ through integration, integrative system biology creates predictive models of cells, organs, biochemical processes and complete organisms, in addition to identifying human disease biomarkers. Recent development in high-throughput methods enables analysis of genome, transcriptome, proteome, and metabolome at an unprecedented scale, thus contributing to the deluge of experimental data in numerous public databases. Several integrative system biology approaches have been developed and applied to the discovery of disease biomarkers from databases. In this review, we highlight several of these approaches and identify future steps in the context of the field of integrative system biology.

Cite this article as:

Zhang Haiyuan, Hu Hao, Deng Cao, Chun Yeona, Zhou Shengtao, Huang Fuqiang and Zhou Qin, Integrative System Biology Strategies for Disease Biomarker Discovery, Combinatorial Chemistry & High Throughput Screening 2012; 15 (4) . https://dx.doi.org/10.2174/138620712799361852