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

Bioinformatics
Junjie ChenBin Liu

Abstract

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

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Citations

Aug 24, 2018·International Journal of Molecular Sciences·Yumeng LiuBin Liu
Aug 29, 2018·PLoS Biology·Nicolas FioriniZhiyong Lu
Jan 23, 2019·Bioinformatics·Ke YanBin Liu
Oct 3, 2019·Protein and Peptide Letters·Lei XuChangrui Liao
Jan 20, 2018·Scientific Reports·Asma EhsanKuo-Chen Chou
Dec 10, 2019·Briefings in Bioinformatics·Bin LiuKe Yan
May 7, 2019·Frontiers in Microbiology·Kaiyang QuQuan Zou
Jan 18, 2021·Briefings in Bioinformatics·Xiaoqing RuQuan Zou
Feb 25, 2020·Computers in Biology and Medicine·Xiaoqing RuQuan Zou
May 8, 2021·Computational Biology and Chemistry·Sayed Mehedi AzimSwakkhar Shatabda
Jan 31, 2019·Journal of Proteome Research·Yanjuan LiQuan Zou
Nov 4, 2021·Briefings in Bioinformatics·Fuyi LiJiangning Song

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