Title
ProtDec-LTR2.0: an improved method for protein remote homology detection by combining pseudo protein and supervised Learning to Rank
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.
Year
DOI
Venue
2017
10.1093/bioinformatics/btx429
BIOINFORMATICS
Field
DocType
Volume
Data mining,Protein sequence analysis,Computer science,Login,Supervised learning,Homology (biology),Bioinformatics,Multiple sequence alignment,Basic research,Web server
Journal
33
Issue
ISSN
Citations 
21
1367-4803
6
PageRank 
References 
Authors
0.43
7
4
Name
Order
Citations
PageRank
Junjie Chen16817.18
Guo M.261.10
Li Shumin3202.02
Bin Liu441933.30