Abstract
Biological networks play a significant role in addressing biological problems. Random walk model is a highly efficient way to study networkswhich has been widely used in solving biological problems based on networks. In this work, those biological problems are classified into four categories, ranking nodes in biological networks, measuring similarity or distance between nodes in biological networks, detecting models from biological networks and finding interrelationship between nodes from different biological networks. After that, we survey the recent advance in applications of random walk models to solve these types of problems on the basis of biological networks.
Keywords: Biological networks, essential proteins, disease genes, protein functions, protein complexes, random walk model.
Current Bioinformatics
Title:Applications of Random Walk Model on Biological Networks
Volume: 11 Issue: 2
Author(s): Wei Peng, Jianxin Wang, Zhen Zhang and Fang-Xiang Wu
Affiliation:
Keywords: Biological networks, essential proteins, disease genes, protein functions, protein complexes, random walk model.
Abstract: Biological networks play a significant role in addressing biological problems. Random walk model is a highly efficient way to study networkswhich has been widely used in solving biological problems based on networks. In this work, those biological problems are classified into four categories, ranking nodes in biological networks, measuring similarity or distance between nodes in biological networks, detecting models from biological networks and finding interrelationship between nodes from different biological networks. After that, we survey the recent advance in applications of random walk models to solve these types of problems on the basis of biological networks.
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Cite this article as:
Peng Wei, Wang Jianxin, Zhang Zhen and Wu Fang-Xiang, Applications of Random Walk Model on Biological Networks, Current Bioinformatics 2016; 11 (2) . https://dx.doi.org/10.2174/1574893611666160223200823
DOI https://dx.doi.org/10.2174/1574893611666160223200823 |
Print ISSN 1574-8936 |
Publisher Name Bentham Science Publisher |
Online ISSN 2212-392X |
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