Reverse engineering of gene regulatory networks from biological data

Authors:
Li-Zhi Liu;Fang-Xiang Wu;Wen-Jun Zhang
Affiliations:
Department of Mechanical Engineering, College of Engineering, University of Saskatchewan, Saskatoon, Saskatchewan, Canada;Department of Mechanical Engineering, College of Engineering, University of Saskatchewan, Saskatoon, Saskatchewan, Canada and Division of Biomedical Engineering, College of Engineering, University ...;Department of Mechanical Engineering, College of Engineering, University of Saskatchewan, Saskatoon, Saskatchewan, Canada and Division of Biomedical Engineering, College of Engineering, University ...
Venue:
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Year:
2012

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Abstract

Reverse engineering of gene regulatory networks (GRNs) is one of the most challenging tasks in systems biology and bioinformatics. It aims at revealing network topologies and regulation relationships between components from biological data. Owing to the development of biotechnologies, various types of biological data are collected from experiments. With the availability of these data, many methods have been developed to infer GRNs. This paper firstly provides an introduction to the basic biological background and the general idea of GRN inferences. Then, different methods are surveyed from two aspects: models that those methods are based on and inference algorithms that those methods use. The advantages and disadvantages of these models and algorithms are discussed. © 2012 Wiley Periodicals, Inc. © 2012 Wiley Periodicals, Inc.