A graph regularized non-negative matrix factorization method for identifying microRNA-disease associations-Reference-Cited by-同舟云学术

A graph regularized non-negative matrix factorization method for identifying microRNA-disease associations

Published:2017-09-01 Issue:2 Volume:34 Page:239-248
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Xiao Qiu¹^ORCID,Luo Jiawei¹,Liang Cheng²,Cai Jie¹,Ding Pingjian¹

Affiliation:

1. College of Computer Science and Electronic Engineering, Hunan University, Changsha, China

2. College of Information Science and Engineering, Shandong Normal University, Jinan, China

Funder

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/article-pdf/34/2/239/25114228/btx545.pdf

Reference49 articles.

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2. RWRMDA: predicting novel human microRNA-disease associations;Chen;Mol. Biosyst,2012

3. WBSMDA: within and between score for MiRNA-disease association prediction;Chen;Sci. Rep. UK,2016

4. Joint analysis of expression profiles from multiple cancers improves the identification of microRNA-gene interactions;Chen;Bioinformatics,2013

5. Semi-supervised learning for potential human microRNA-disease association inference;Chen;Sci. Rep,2014

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