A random forest based computational model for predicting novel lncRNA-disease associations

A random forest based computational model for predicting novel lncRNA-disease associations

Abstract Background Accumulated evidence shows that the abnormal regulation of long non-coding RNA (lncRNA) is associated with various human diseases. Accurately identifying disease-associated lncRNAs is helpful to study the mechanism of lncRNAs in diseases and explore new therapies of diseases. Man...

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Bibliographic Details
Main Authors: Dengju Yao, Xiaojuan Zhan, Xiaorong Zhan, Chee Keong Kwoh, Peng Li, Jinke Wang
Format: Article
Language:English
Published: BMC 2020-03-01
Series:BMC Bioinformatics
Subjects:
Random forest
Variable importance
Feature selection
lncRNA-disease association prediction
Bioinformatics algorithm
Online Access:http://link.springer.com/article/10.1186/s12859-020-3458-1

Internet

http://link.springer.com/article/10.1186/s12859-020-3458-1

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