An ab initio lncRNA identification and functional annotation tool based on deep learning
Long noncoding RNAs (lncRNAs) play important biological roles and have been implicated in human diseases. To characterize lncRNAs, identifying and annotating lncRNAs is necessary. Here, we propose a novel lncRNA identification and functional annotation tool named LncADeep. First, LncADeep identifies lncRNAs by integrating sequence intrinsic and homology features based on deep belief networks. Second, LncADeep predicts lncRNA-protein interactions using sequence and structure features based on deep neural networks. Third, since accurate lncRNA-protein interactions can help to infer the functions of lncRNAs, LncADeep conducts KEGG and Reactome pathway enrichment analysis and functional module detection with the predicted interacting proteins of lncRNAs. Case studies show that LncADeep's annotations for lncRNAs comply with their known functions. As a tool for lncRNA identification and functional annotation based on deep learning, LncADeep has outperformed state-of-the-art tools on predicting lncRNAs and lncRNA-protein interactions, and can automatically provide informative functional annotations for lncRNAs.
- LncADeep 1.0 (Tested on Linux_64, including CentOS 6.5 and Ubuntu 16.04)
Release version: LncADeep_v1.0
- Functional annotations for the lncRNAs collected in GENCODE v24.
Cheng Yang, Longshu Yang, Man Zhou, Haoling Xie, Chengjiu Zhang, May D Wang, Huaiqiu Zhu; LncADeep: An ab initio lncRNA identification and functional annotation tool based on deep learning, Bioinformatics, 2018, bty428
Please direct your questions to: Dr. Huaiqiu Zhu, email@example.com