EPSVR / EPMeta – Prediction of Antigenic Epitopes

EPSVR / EPMeta

:: DESCRIPTION

EPSVR is a server application for discontinuous epitope prediction which uses a Support Vector Regression (SVR) method to integrate six scoring terms.

EPMeta is a Meta Server for Prediction of Antigenic Epitopes.

::DEVELOPER

System Biology Laboratory Of Chi Zhang

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 EPMeta

 :: MORE INFORMATION

Citation

BMC Bioinformatics. 2010 Jul 16;11:381. doi: 10.1186/1471-2105-11-381.
EPSVR and EPMeta: prediction of antigenic epitopes using support vector regression and multiple server results.
Liang S1, Zheng D, Standley DM, Yao B, Zacharias M, Zhang C.

EPCES – Prediction of Antigenic Epitopes on Protein Surfaces by Consensus Scoring

EPCES

:: DESCRIPTION

EPCES (Epitopes ConsEnsus Scoring) is a new antigen Epitope Prediction method from six different scoring functions – residue epitope propensity, conservation score, side-chain energy score, contact number, surface planarity score, and secondary structure composition.

::DEVELOPER

System Biology Laboratory Of Chi Zhang

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

 :: MORE INFORMATION

Citation

BMC Bioinformatics. 2009 Sep 22;10:302. doi: 10.1186/1471-2105-10-302.
Prediction of antigenic epitopes on protein surfaces by consensus scoring.
Liang S1, Zheng D, Zhang C, Zacharias M.

SVMTriP – prediction of Antigenic Epitopes

SVMTriP

:: DESCRIPTION

SVMTriP (Support Vector Machine, Tri-peptide similarity and Propensity scores) is a method to predict antigenic epitopes using support vector machine to integrate tri-peptide similarity and propensity.

::DEVELOPER

System Biology Laboratory Of Chi Zhang

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

 :: MORE INFORMATION

Citation

PLoS One. 2012;7(9):e45152. doi: 10.1371/journal.pone.0045152. Epub 2012 Sep 12.
SVMTriP: a method to predict antigenic epitopes using support vector machine to integrate tri-peptide similarity and propensity.
Yao B1, Zhang L, Liang S, Zhang C.