TY - GEN
T1 - Prioritizing disease genes by bi-random walk
AU - Xie, Maoqiang
AU - Hwang, Taehyun
AU - Kuang, Rui
PY - 2012
Y1 - 2012
N2 - Random walk methods have been successfully applied to prioritizing disease causal genes. In this paper, we propose a bi-random walk algorithm (BiRW) based on a regularization framework for graph matching to globally prioritize disease genes for all phenotypes simultaneously. While previous methods perform random walk either on the protein-protein interaction network or the complete phenome-genome heterogenous network, BiRW performs random walk on the Kronecker product graph between the protein-protein interaction network and the phenotype similarity network. Three variations of BiRW that perform balanced or unbalanced bi-directional random walks are analyzed and compared with other random walk methods. Experiments on analyzing the disease phenotype-gene associations in Online Mendelian Inheritance in Man (OMIM) demonstrate that BiRW effectively improved disease gene prioritization over existing methods by ranking more known associations in the top 100 out of nearly 10,000 candidate genes.
AB - Random walk methods have been successfully applied to prioritizing disease causal genes. In this paper, we propose a bi-random walk algorithm (BiRW) based on a regularization framework for graph matching to globally prioritize disease genes for all phenotypes simultaneously. While previous methods perform random walk either on the protein-protein interaction network or the complete phenome-genome heterogenous network, BiRW performs random walk on the Kronecker product graph between the protein-protein interaction network and the phenotype similarity network. Three variations of BiRW that perform balanced or unbalanced bi-directional random walks are analyzed and compared with other random walk methods. Experiments on analyzing the disease phenotype-gene associations in Online Mendelian Inheritance in Man (OMIM) demonstrate that BiRW effectively improved disease gene prioritization over existing methods by ranking more known associations in the top 100 out of nearly 10,000 candidate genes.
KW - Bi-Random Walk
KW - Disease Gene Prioritization
KW - Graph-based Learning
UR - http://www.scopus.com/inward/record.url?scp=84861429944&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84861429944&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-30220-6_25
DO - 10.1007/978-3-642-30220-6_25
M3 - Conference contribution
AN - SCOPUS:84861429944
SN - 9783642302190
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 292
EP - 303
BT - Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference, PAKDD 2012, Proceedings
T2 - 16th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2012
Y2 - 29 May 2012 through 1 June 2012
ER -