电子学报2023，Vol.51Issue(10)：2866-2873,8.DOI:10.12263/DZXB.20211197
基于网络嵌入的癌症性状hub基因发现
Hub Gene Discovery of Cancer Traits Based on Network Embedding
摘要
Abstract
The research on hub genes affecting cancer traits has such problems:only focusing on strong correlation genes for gene information processing,lack of the co-expression of weak correlation genes and different gene modules;only using degree centrality to judge hub genes to analyze gene network,not comprehensive enough for implicit data mining.This paper proposes the graph embedding algorithm Gene2vec based on information walk with gene module label.The appropriate soft threshold to retain more weakly correlated gene information is selected.The gene module co-expression network is formed by combining different kinds of gene modules with high positive correlation traits.Aiming to solve the problems of mining gene module network information by traditional weighted gene co-expression network analysis method and graph embedding method,the paper adjust the random walk process in the gene module network by label parameters and other parameters and analyze the node sequence generated random walk to mine the gene network information.Experi-ments show that Gene2vec is better than other algorithms in the hub gene's detection rate,and the hub gene expression in cancer traits is higher than that of the hub gene obtained by common biological methods.关键词
hub基因/数据挖掘/信息游走/网络嵌入/加权基因共表达网络分析Key words
hub gene/data mining/information walk/network embedding/weighted gene co-expression network analysis分类
信息技术与安全科学引用本文复制引用
初妍,戚书豪,张薇,王瀚麟,李松..基于网络嵌入的癌症性状hub基因发现[J].电子学报,2023,51(10):2866-2873,8.基金项目
黑龙江省属高校基本科研业务费基础研究项目(No.2021-KYYWF-0043)Basic Research Business Fee Basic Research Project of Heilongjiang Provincial Universities(No.2021-KYYWF-0043) （No.2021-KYYWF-0043）
