Biased random walk with restart for essential proteins prediction
Biased random walk with restart for essential proteins prediction作者机构：School of Computer and CommunicationLanzhou University of TechnologyLanzhou 730050China China Mobile Communications Group Gansu Co.Ltd.Lanzhou 730070China
出 版 物：《Chinese Physics B》 (中国物理B（英文版）)
年 卷 期：2022年第31卷第11期
页 面：638-648页
核心收录：
学科分类：02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 07[理学] 070205[理学-凝聚态物理] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 0701[理学-数学] 0702[理学-物理学]
主 题：PPI network essential proteins random walk with restart gene expression
摘 要：Predicting essential proteins is crucial for discovering the process of cellular organization and *** propose biased random walk with restart algorithm for essential proteins prediction,called ***,the common process of practice walk often sets the probability of particles transferring to adjacent nodes to be equal,neglecting the influence of the similarity structure on the transition *** address this problem,we redefine a novel transition probability matrix by integrating the gene express similarity and subcellular location *** particles can obtain biased transferring probabilities to perform random walk so as to further exploit biological properties embedded in the network ***,we use gene ontology(GO)terms score and subcellular score to calculate the initial probability vector of the random walk with ***,when the biased random walk with restart process reaches steady state,the protein importance score is *** order to demonstrate superiority of BRWR,we conduct experiments on the YHQ,BioGRID,Krogan and Gavin PPI *** results show that the method BRWR is superior to other state-of-the-art methods in essential proteins recognition ***,compared with the contrast methods,the improvements of BRWR in terms of the ACC results range in 1.4%–5.7%,1.3%–11.9%,2.4%–8.8%,and 0.8%–14.2%,***,BRWR is effective and reasonable.
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