Affiliation:
1. School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China
Abstract
In view of time delay existing in gene regulation, by using the analysis idea and methods of complex network, this paper proposes a multi-time-delay gene regulation network analysis method based on the fuzzy label propagation. The algorithm takes the relative change trend coefficient, the correlation coefficient, and the mutual information as the similarity measurement indexes for the gene pair, fully reflecting the correlation of gene pairs and simultaneously obtaining the gene regulation relationship and the time delay through the fuzzy label propagation algorithm of the semisupervised learning. Experimental results of the cell cycle-regulated genes of yeast show that the proposed construction method of GRN can not only correctly select potential regulation genes but also provide details about the gene regulator model, thereby more accurately constructing gene regulation network.
Funder
National Natural Science Foundation of China
Subject
Health Informatics,Biomedical Engineering,Surgery,Biotechnology
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. A Semi-Supervised Approach to GRN Inference Using Learning and Optimization;Research Anthology on Bioinformatics, Genomics, and Computational Biology;2023-12-29
2. A Semi-Supervised Approach to GRN Inference Using Learning and Optimization;International Journal of Applied Metaheuristic Computing;2021-10