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Table 1 Attributes of and citations for the epitope prediction programs used

From: Using epitope predictions to evaluate efficacy and population coverage of the Mtb72f vaccine for tuberculosis

Program

Prediction method

Unique features

Source paper (number of citations 1 )

URL

ARB

Average relative binding matrices

 

[42] (59)

[43]

MHCPred

Partial least squares

 

[33] (46)

[44]

   

[34] (30)

 
   

[35] (30)

 

ProPred

Matrix-based

TEPITOPE matrices; requires key anchor residues

[45] (186)

[41]

   

TEPITOPE: [30] (310)

 

RankPep

Position Specific

 

[23] (119)

[47]

 

Scoring Matrices

 

[46] (102)

 

NetMHCII

Position Specific Scoring Matrices

Predicts epitopes of multiple lengths; uses SMM-align matrices

[37] (29)

[48]

SVRMHC

Support vector machine regression

 

[32] (16)

[49]

   

[31] (23)

 

Vaxign

Position Specific Scoring Matrices

 

[40] (0)

[50]

NetMHCIIpan

Artificial Neural Networks

Predicts multiple-length epitope binding to every sequenced Class II allele

[11] (3)

[51]

  1. 1 Citation numbers are from Google Scholar