Uncover miRNA-Disease Association by Exploiting Global Network Similarity.
Identification of miRNA-disease association is a fundamental challenge in human health clinic. However, the known miRNA-disease associations are rare and experimental verification methods are expensive and time-consuming. Therefore, there is a strong incentive to develop computational methods. In th...
Main Authors: | Min Chen, Xingguo Lu, Bo Liao, Zejun Li, Lijun Cai, Changlong Gu |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2016-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC5132253?pdf=render |
Similar Items
-
LRMCMDA: Predicting miRNA-Disease Association by Integrating Low-Rank Matrix Completion With miRNA and Disease Similarity Information
by: Junlin Xu, et al.
Published: (2020-01-01) -
Dysregulation of miRNA in Leukemia: Exploiting miRNA Expression Profiles as Biomarkers
by: Luisa Anelli, et al.
Published: (2021-07-01) -
SRMDAP: SimRank and Density-Based Clustering Recommender Model for miRNA-Disease Association Prediction
by: Xiaoying Li, et al.
Published: (2018-01-01) -
Integrating miRNA and mRNA Expression Profiling Uncovers miRNAs Underlying Fat Deposition in Sheep
by: Guangxian Zhou, et al.
Published: (2017-01-01) -
Improved Pre-miRNAs Identification Through Mutual Information of Pre-miRNA Sequences and Structures
by: Xiangzheng Fu, et al.
Published: (2019-02-01)