LDAP: a web server for lncRNA-disease association prediction

被引：182

作者：

Lan, Wei ^{[1
]}

Li, Min ^{[1
]}

Zhao, Kaijie ^{[1
]}

Liu, Jin ^{[1
]}

Wu, Fang-Xiang ^{[2
]}

Pan, Yi ^{[3
]}

Wang, Jianxin ^{[1
]}

机构：

[1] Cent S Univ, Sch Informat Sci & Engn, Changsha 410083, Hunan, Peoples R China

[2] Univ Saskatchewan, Div Biomed Engn, Saskatoon, SK S7N 5A9, Canada

[3] Georgia State Univ, Dept Comp Sci, Atlanta, GA 30302 USA

来源：

BIOINFORMATICS | 2017年 / 33卷 / 03期

基金：

中国国家自然科学基金;

关键词：

BREAST; CANCER;

D O I：

10.1093/bioinformatics/btw639

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Motivation: Increasing evidences have demonstrated that long noncoding RNAs (lncRNAs) play important roles in many human diseases. Therefore, predicting novel lncRNA-disease associations would contribute to dissect the complex mechanisms of disease pathogenesis. Some computational methods have been developed to infer lncRNA-disease associations. However, most of these methods infer lncRNA-disease associations only based on single data resource. Results: In this paper, we propose a new computational method to predict lncRNA-disease associations by integrating multiple biological data resources. Then, we implement this method as a web server for lncRNA-disease association prediction (LDAP). The input of the LDAP server is the lncRNA sequence. The LDAP predicts potential lncRNA-disease associations by using a bagging SVM classifier based on lncRNA similarity and disease similarity.

引用

页码：458 / 460

页数：3

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