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Modules in Biological Networks: Identification and Application

Modules in Biological Networks: Identification and Application

Bing Zhang, Zhiao Shi
Copyright: © 2011 |Pages: 27
ISBN13: 9781609604912|ISBN10: 1609604911|EISBN13: 9781609604929
DOI: 10.4018/978-1-60960-491-2.ch011
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MLA

Zhang, Bing, and Zhiao Shi. "Modules in Biological Networks: Identification and Application." Handbook of Research on Computational and Systems Biology: Interdisciplinary Applications, edited by Limin Angela Liu, et al., IGI Global, 2011, pp. 248-274. https://doi.org/10.4018/978-1-60960-491-2.ch011

APA

Zhang, B. & Shi, Z. (2011). Modules in Biological Networks: Identification and Application. In L. Liu, D. Wei, Y. Li, & H. Lei (Eds.), Handbook of Research on Computational and Systems Biology: Interdisciplinary Applications (pp. 248-274). IGI Global. https://doi.org/10.4018/978-1-60960-491-2.ch011

Chicago

Zhang, Bing, and Zhiao Shi. "Modules in Biological Networks: Identification and Application." In Handbook of Research on Computational and Systems Biology: Interdisciplinary Applications, edited by Limin Angela Liu, et al., 248-274. Hershey, PA: IGI Global, 2011. https://doi.org/10.4018/978-1-60960-491-2.ch011

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Abstract

One of the most prominent properties of networks representing complex systems is modularity. Network-based module identification has captured the attention of a diverse group of scientists from various domains and a variety of methods have been developed. The ability to decompose complex biological systems into modules allows the use of modules rather than individual genes as units in biological studies. A modular view is shaping research methods in biology. Module-based approaches have found broad applications in protein complex identification, protein function prediction, protein expression prediction, as well as disease studies. Compared to single gene-level analyses, module-level analyses offer higher robustness and sensitivity. More importantly, module-level analyses can lead to a better understanding of the design and organization of complex biological systems.

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