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Genomics Proteomics Bioinformatics. 2014 Oct;12(5):210-20. doi: 10.1016/j.gpb.2014.10.002. Epub 2014 Oct 28.

Pathway-based analysis tools for complex diseases: a review.

Author information

1
Institute for Medical Systems Biology, and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China.
2
Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
3
Community Health Service Management Center of Panyu District, Guangzhou 511400, China.
4
Department of Statistical Sciences, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275, China.
5
Institute for Medical Systems Biology, and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China; Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China; Department of Statistical Sciences, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275, China. Electronic address: raoshaoq@gdmc.edu.cn.

Abstract

Genetic studies are traditionally based on single-gene analysis. The use of these analyses can pose tremendous challenges for elucidating complicated genetic interplays involved in complex human diseases. Modern pathway-based analysis provides a technique, which allows a comprehensive understanding of the molecular mechanisms underlying complex diseases. Extensive studies utilizing the methods and applications for pathway-based analysis have significantly advanced our capacity to explore large-scale omics data, which has rapidly accumulated in biomedical fields. This article is a comprehensive review of the pathway-based analysis methods-the powerful methods with the potential to uncover the biological depths of the complex diseases. The general concepts and procedures for the pathway-based analysis methods are introduced and then, a comprehensive review of the major approaches for this analysis is presented. In addition, a list of available pathway-based analysis software and databases is provided. Finally, future directions and challenges for the methodological development and applications of pathway-based analysis techniques are discussed. This review will provide a useful guide to dissect complex diseases.

KEYWORDS:

Algorithms; Complex disease; Pathway-based analysis; Software and databases

PMID:
25462153
PMCID:
PMC4411419
DOI:
10.1016/j.gpb.2014.10.002
[Indexed for MEDLINE]
Free PMC Article

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