Improved low-rank matrix recovery method for predicting miRNA-disease association
Abstract MicroRNAs (miRNAs) performs crucial roles in various human diseases, but miRNA-related pathogenic mechanisms remain incompletely understood. Revealing the potential relationship between miRNAs and diseases is a critical problem in biomedical research. Considering limitation of existing comp...
Saved in:
Main Authors: | Li Peng, Manman Peng, Bo Liao, Guohua Huang, Wei Liang, Keqin Li |
---|---|
Format: | article |
Language: | EN |
Published: |
Nature Portfolio
2017
|
Subjects: | |
Online Access: | https://doaj.org/article/f4af1f5773e542e4858c49bbf482e52f |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
IMDAILM: Inferring miRNA-Disease Association by Integrating lncRNA and miRNA Data
by: Yuhua Yao, et al.
Published: (2020) -
Trehalose significantly enhances the recovery of serum and serum exosomal miRNA from a paper-based matrix
by: Shu Hui Neo, et al.
Published: (2017) -
Fast Construction of the Radio Map Based on the Improved Low-Rank Matrix Completion and Recovery Method for an Indoor Positioning System
by: Zhuang Wang, et al.
Published: (2021) -
Bipartite graph-based collaborative matrix factorization method for predicting miRNA-disease associations
by: Feng Zhou, et al.
Published: (2021) -
Impact of host genes and strand selection on miRNA and miRNA* expression.
by: Marta Biasiolo, et al.
Published: (2011)