Please use this identifier to cite or link to this item: https://doi.org/10.3390/molecules23102439
Title: Inferring microRNA-environmental factor interactions based on multiple biological information fusion
Authors: Luo, H
Lan, W
Chen, Q 
Wang, Z
Liu, Z
Yue, X
Zhu, L
Keywords: biological product
microRNA
algorithm
biology
chemistry
gene expression regulation
genetics
human
metabolism
procedures
Algorithms
Biological Products
Computational Biology
Gene Expression Regulation
Humans
MicroRNAs
Issue Date: 2018
Publisher: MDPI AG
Citation: Luo, H, Lan, W, Chen, Q, Wang, Z, Liu, Z, Yue, X, Zhu, L (2018). Inferring microRNA-environmental factor interactions based on multiple biological information fusion. Molecules 23 (10) : 2439. ScholarBank@NUS Repository. https://doi.org/10.3390/molecules23102439
Rights: Attribution 4.0 International
Abstract: Accumulated studies have shown that environmental factors (EFs) can regulate the expression of microRNA (miRNA) which is closely associated with several diseases. Therefore, identifying miRNA-EF associations can facilitate the study of diseases. Recently, several computational methods have been proposed to explore miRNA-EF interactions. In this paper, a novel computational method, MEI-BRWMLL, is proposed to uncover the relationship between miRNA and EF. The similarities of miRNA-miRNA are calculated by using miRNA sequence, miRNA-EF interaction, and the similarities of EF-EF are calculated based on the anatomical therapeutic chemical information, chemical structure and miRNA-EF interaction. The similarity network fusion is used to fuse the similarity between miRNA and the similarity between EF, respectively. Further, the multiple-label learning and bi-random walk are employed to identify the association between miRNA and EF. The experimental results show that our method outperforms the state-of-the-art algorithms. © 2018 MDPI AG. All rights reserved.
Source Title: Molecules
URI: https://scholarbank.nus.edu.sg/handle/10635/179023
ISSN: 14203049
DOI: 10.3390/molecules23102439
Rights: Attribution 4.0 International
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