Integrative identification of core genetic regulatory modules via a structural model-based clustering method. (1st January 2011)

• Record Type: Journal Article
• Authors: Tang, Binhua; Chen, Su-Shing; Jin, Victor X.
• Is Part Of: International journal of computational biology and drug design. Volume 4:Number 2(2011)
• Page Start: 127
• Page End: 146
• Publication Date: 2011-01-01
• Subjects: genetic regulatory module -- structural model clustering -- dynamic models; Computational biology -- Periodicals; Drugs -- Design -- Periodicals; 570.285
• DOI: 10.1504/IJCBDD.2011.041007
• Languages: English
• ISSNs: 1756-0756

Abstract

Regulatory modules play fundamental roles in processing and dispatching signals in cell life cycle. Although current clustering methods may reduce data complexity to lower dimension, they tend to neglect biological meanings within high-throughput data. We propose a module-detection algorithm through defining network activity measures and associating them through a weighted clustering approach. We verify our method on diverse models and it provides a unique perspective for analysing model dynamics and expression data, especially with consideration of inherent biological meanings. As it can detect core regulatory modules effectively, it facilitates pathway/network modelling in systems biology.