miRNA-disease association prediction with collaborative matrix factorization
type: Item
instance of: scholarly article
title: miRNA-disease association prediction with collaborative matrix factorization
zbMATH Open document ID: 1377.92048
DOI: 10.1155/2017/2498957
author: Zhen Shen
author: You-Hua Zhang
author: Kyungsook Han
author: Asoke Kumar Nandi
author: Barry Honig
author: De-Shuang Huang
published in: Complexity
publication date: 2018-01-05T00:00:00Z
review text: Summary: As one of the factors in the noncoding RNA family, microRNAs (miRNAs) are involved in the development and progression of various complex diseases. Experimental identification of miRNA-disease association is expensive and time-consuming. Therefore, it is necessary to design efficient algorithms to identify novel miRNA-disease association. In this paper, we develop the computational method of Collaborative Matrix Factorization for miRNA-Disease Association prediction (CMFMDA) to identify potential miRNA-disease associations by integrating miRNA functional similarity, disease semantic similarity, and experimentally verified miRNA-disease associations. Experiments verifiy that CMFMDA achieves intended purpose and application values with its short consuming-time and high prediction accuracy. In addition, we use CMFMDA on Esophageal Neoplasms and Kidney Neoplasms to reveal their potential related miRNAs. As a result, 84\% and 82\% of top 50 predicted miRNA-disease pairs for these two diseases are confirmed by experiment. Not only this, but also CMFMDA could be applied to new diseases and new miRNAs without any known associations, which overcome the defects of many previous computational methods.
Mathematics Subject Classification ID: 92C50
Mathematics Subject Classification ID: 92D20
Mathematics Subject Classification ID: 93B07
Mathematics Subject Classification ID: 93B40
zbMATH DE Number: 6822304
zbMATH Keywords: microRNA-disease association prediction
zbMATH Keywords: collaborative matrix factorization
describes a project that uses: SFAPS
describes a project that uses: RBMMMDA
describes a project that uses: miRBase
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2017/2498957
OpenAlex ID: W2757038198
description: scientific article; zbMATH DE number 6822304