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

doi:10.1093/bioinformatics/btx429

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

Harbin Institute of Technology

Research output: Contribution to journal › Article › peer-review

40 Citations (Scopus)

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: bliu@hit.edu.cn.

Original language	English
Pages (from-to)	3473-3476
Number of pages	4
Journal	Bioinformatics
Volume	33
Issue number	21
DOIs	https://doi.org/10.1093/bioinformatics/btx429
Publication status	Published - 1 Nov 2017
Externally published	Yes

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10.1093/bioinformatics/btx429

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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: bliu@hit.edu.cn.",

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AU - Liu, Bin

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AB - 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: bliu@hit.edu.cn.

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

Abstract

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