Literature DB >> 29077805

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

Junjie Chen1, Mingyue Guo1, Shumin Li1, Bin Liu1.   

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.
© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

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Year:  2017        PMID: 29077805     DOI: 10.1093/bioinformatics/btx429

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  8 in total

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Journal:  PLoS Biol       Date:  2018-08-28       Impact factor: 8.029

5.  Protein remote homology detection based on bidirectional long short-term memory.

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Journal:  BMC Bioinformatics       Date:  2017-10-10       Impact factor: 3.169

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Review 7.  Application of Machine Learning in Microbiology.

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Journal:  Front Genet       Date:  2019-09-18       Impact factor: 4.599

  8 in total

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