General Information
| Description | A web server for lncRNA-disease association prediction |
| Homepage | http://bioinformatics.csu.edu.cn/ldap |
Publications
LDAP: a web server for lncRNA-disease association prediction
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.
Availability and Implementation:
The web server is available at http://bioinformatics.csu.edu.cn/ldap
Contact:
jxwang@mail.csu.edu.cn.
Supplementary information:
Supplementary data are available at Bioinformatics online.
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