ProtDec-LTR2.0: an improved method for protein remote homology detection by combining pseudo protein and supervised Learning to Rank.

Junjie Chen, Mingyue Guo, Shumin Li, Bin Liu

Journal: Bioinformatics (Oxford, England) 2018;33(21):3473-3476

PMID: 29077805

Full Text on Ovid Technologies, Inc. View on PubMed

Abstract

SUMMARY

As one of the most important tasks in protein sequence analysis, protein remote homology detection is critical for both basic research and practical applications. Here, we present an effective web server for protein remote homology detection called ProtDec-LTR2.0 by combining ProtDec-Learning to Rank (LTR) and pseudo protein representation. Experimental results showed that the detection performance is obviously improved. The web server provides a user-friendly interface to explore the sequence and structure information of candidate proteins and find their conserved domains by launching a multiple sequence alignment tool.

AVAILABILITY AND IMPLEMENTATION

The web server is free and open to all users with no login requirement at http://bioinformatics.hitsz.edu.cn/ProtDec-LTR2.0/.

CONTACT

[email protected].

Address: School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong 518055, China.

DOI: 10.1093/bioinformatics/btx429