Abstract
Recent advances in proteomic and transcriptomic technologies resulted in the accumulation of vast amount of high-throughput data that span multiple biological processes and characteristics in different organisms. Much of the data come in the form of interaction networks and mRNA expression arrays. An important task in systems biology is functional modules discovery where the goal is to uncover well-connected sub-networks (modules). These discovered modules help to unravel the underlying mechanisms of the observed biological processes. While most of the existing module discovery methods use only the interaction data, in this work we propose, CLARM, which discovers biological modules by incorporating gene profiles data with protein-protein interaction networks. We demonstrate the effectiveness of CLARM on Yeast and Human interaction datasets, and gene expression and molecular function profiles. Experiments on these real datasets show that the CLARM approach is competitive to well established functional module discovery methods.
Keywords: Biological processes, CLARM, expression arrays, functional modules, interaction proteomic, sub-networks.
Current Bioinformatics
Title:Improving Functional Modules Discovery by Enriching Interaction Networks with Gene Profiles
Volume: 8 Issue: 3
Author(s): Saeed Salem, Rami Alroobi, Shadi Banitaan, Loqmane Seridi, Ibrahim Aljarah and James Brewer
Affiliation:
Keywords: Biological processes, CLARM, expression arrays, functional modules, interaction proteomic, sub-networks.
Abstract: Recent advances in proteomic and transcriptomic technologies resulted in the accumulation of vast amount of high-throughput data that span multiple biological processes and characteristics in different organisms. Much of the data come in the form of interaction networks and mRNA expression arrays. An important task in systems biology is functional modules discovery where the goal is to uncover well-connected sub-networks (modules). These discovered modules help to unravel the underlying mechanisms of the observed biological processes. While most of the existing module discovery methods use only the interaction data, in this work we propose, CLARM, which discovers biological modules by incorporating gene profiles data with protein-protein interaction networks. We demonstrate the effectiveness of CLARM on Yeast and Human interaction datasets, and gene expression and molecular function profiles. Experiments on these real datasets show that the CLARM approach is competitive to well established functional module discovery methods.
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Cite this article as:
Salem Saeed, Alroobi Rami, Banitaan Shadi, Seridi Loqmane, Aljarah Ibrahim and Brewer James, Improving Functional Modules Discovery by Enriching Interaction Networks with Gene Profiles, Current Bioinformatics 2013; 8 (3) . https://dx.doi.org/10.2174/1574893611308030008
DOI https://dx.doi.org/10.2174/1574893611308030008 |
Print ISSN 1574-8936 |
Publisher Name Bentham Science Publisher |
Online ISSN 2212-392X |
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