Submit Manuscript  

Article Details


Random Walks On Biomedical Networks

Author(s):

Guiyang Zhang, Pan Wang, You Li and Guohua Huang*   Pages 1 - 12 ( 12 )

Abstract:


The biomedical network is becoming a fundamental tool to represent sophisticated bio-systems, while random walk models on it are becoming a sharp sword to address such challenging issues as gene function annotation, drug target identification, and disease biomarker recognition. Recently, numerous random walk models have been proposed and applied to biomedical networks. Due to good performances, the random walk is increasingly attracting more and more attention from multiple communities. In this survey, we firstly introduced various random walk models, with emphasis on the Pag-eRank and the random walk with restart. We then summarized applications of the RW on the biomedical networks from the graph learning point of view, which mainly included node classification, link prediction, cluster/community detection, and learning representation of the node. We discussed briefly its limitation and existing issues also

Keywords:

random walk, network embedding, link prediction, clustering, node classification, node representation

Affiliation:

Provincial Key Laboratory of Informational Service for Rural Area of Southwestern Hunan, Shaoyang University, Shao-yang 422000, Provincial Key Laboratory of Informational Service for Rural Area of Southwestern Hunan, Shaoyang University, Shao-yang 422000, Provincial Key Laboratory of Informational Service for Rural Area of Southwestern Hunan, Shaoyang University, Shao-yang 422000, Provincial Key Laboratory of Informational Service for Rural Area of Southwestern Hunan, Shaoyang University, Shao-yang 422000



Read Full-Text article