miRNA-Disease Association Prediction with Collaborative Matrix Factorization
Joint Authors
Han, Kyungsook
Huang, De-Shuang
Nandi, Asoke K.
Shen, Zhen
Zhang, You-Hua
Honig, Barry
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-09-28
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
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 developed 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 verified that CMFMDA achieves intended purpose and application values with its short consuming-time and high prediction accuracy.
In addition, we used 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 were 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.
American Psychological Association (APA)
Shen, Zhen& Zhang, You-Hua& Han, Kyungsook& Nandi, Asoke K.& Honig, Barry& Huang, De-Shuang. 2017. miRNA-Disease Association Prediction with Collaborative Matrix Factorization. Complexity،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1142640
Modern Language Association (MLA)
Shen, Zhen…[et al.]. miRNA-Disease Association Prediction with Collaborative Matrix Factorization. Complexity No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1142640
American Medical Association (AMA)
Shen, Zhen& Zhang, You-Hua& Han, Kyungsook& Nandi, Asoke K.& Honig, Barry& Huang, De-Shuang. miRNA-Disease Association Prediction with Collaborative Matrix Factorization. Complexity. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1142640
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142640