PreTP-EL – Prediction of Therapeutic Peptides based on Ensemble Learning

PreTP-EL

:: DESCRIPTION

PreTP-EL is a predictor which has been proposed via employing the ensemble learning approach to fuse the different features and machine learning techniques in order to capture the different characteristics of various therapeutic peptides.

::DEVELOPER

Liu Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Guo Y, Yan K, Lv H, Liu B.
PreTP-EL: prediction of therapeutic peptides based on ensemble learning.
Brief Bioinform. 2021 Nov 5;22(6):bbab358. doi: 10.1093/bib/bbab358. PMID: 34459488.

iRSpot-EL – Identify Recombination Spots with an ensemble learning approach

iRSpot-EL

:: DESCRIPTION

iRSpot-EL is a predictor: by fusing different modes of pseudo K-tuple nucleotide composition and mode of dinucleotide-based auto-cross covariance into an ensemble classifier of clustering approach.

::DEVELOPER

Liu Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Liu B, Wang S, Long R, Chou KC.
iRSpot-EL: identify recombination spots with an ensemble learning approach.
Bioinformatics. 2017 Jan 1;33(1):35-41. doi: 10.1093/bioinformatics/btw539. Epub 2016 Aug 16. PMID: 27531102.

enDNA-Prot – Identification of DNA-binding Proteins by Applying Ensemble Learning

enDNA-Prot

:: DESCRIPTION

enDNA-Prot is a web server for DNA-binding protein identification by employing the ensemble learning technique.

::DEVELOPER

Liu Lab, Harbin Institute of Technology Shenzhen Graduate School.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Ruifeng Xu, Jiyun Zhou, Bin Liu, et al.,
“enDNA-Prot: Identification of DNA-binding Proteins by Applying Ensemble Learning,”
BioMed Research International, Vol. 2014, Article ID 294279, 10 pages, 2014, doi:10.1155/2014/294279