ProtDec-LTR 3.0 – Application of Learning to Rank to Protein Remote Homology detection

ProtDec-LTR 3.0

:: DESCRIPTION

ProtDec-LTR is an method for protein remote homology detection by combining pseudo protein and supervised learning to rank

::DEVELOPER

Liu Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Liu B, et al.
ProtDec-LTR3.0: protein remote homology detection by embedding sequence-based features into learning to rank,
IEEE ACCESS 
2019; 7:102499-102507.

Chen J, Guo M, Li S, Liu B.
ProtDec-LTR2.0: an improved method for protein remote homology detection by combining pseudo protein and supervised Learning to Rank.
Bioinformatics. 2017 Nov 1;33(21):3473-3476. doi: 10.1093/bioinformatics/btx429. PMID: 29077805.

Liu B, Chen J, Wang X.
Application of learning to rank to protein remote homology detection.
Bioinformatics. 2015 Nov 1;31(21):3492-8. doi: 10.1093/bioinformatics/btv413. Epub 2015 Jul 10. PMID: 26163693.

dRHP-PseRA – Detecting Remote Homology Proteins using Profile-based Pseudo Protein Sequence and Rank Aggregation

dRHP-PseRA

:: DESCRIPTION

dRHP-PseRA is a new predictor which was developed by combining four state-of-the-art predictors (PSI-BLAST, HHblits, Hmmer, and Coma) via the rank aggregation approach, based on the concept of pseudo proteins.

::DEVELOPER

Liu Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

NO

:: MORE INFORMATION

Citation

Chen J, Long R, Wang XL, Liu B, Chou KC.
dRHP-PseRA: detecting remote homology proteins using profile-based pseudo protein sequence and rank aggregation.
Sci Rep. 2016 Sep 1;6:32333. doi: 10.1038/srep32333. PMID: 27581095; PMCID: PMC5007510.