Links

Direct Links

 

Prediction servers for free

Prediction Server

Description

MHC Class

References

 CTLPred

A SVM and ANN based CTL epitope prediction tool

Class I

1

ProPred1

Promiscuous MHC class-I binding peptide prediction server

Class I

2

MAPPP

MHC-I antigenic peptide processing prediction

Class I

3

nHLAPred

A neural network based MHC class-I binding peptide prediction server

Class I

4

BIMAS

Bioinformatics & molecular analysis section

Class I

5

LPPEP

Linear programming for HLA A2

Class I

6

SVMHC

Support vector machine (SVM)

Class I

7

NetMHC

ANN for HLA A2 and mouse H2K

Class I

8

MHCPred

Quantitative matrices

Class I

9

Epitope binding - obsolete

Quantitative matrices

Class I

10

MMPRED

QM (predict mutated binders)

Class I

11

PREDEP

PSSM (position specific scoring matrices)

Class I

12

T-epitope designer

Virtual pockets in 3D

class I

13

PREDICT - obsolete

Predict is the interface for prediction of peptide binding to MHC molecule

Class I/II

14

SYFPEITHI

motifs matrices (MM)

Class I/II

15

RANKPEP

Predicts peptide binders to MHCI and MHCII molecules from protein sequence/s or sequence alignments using position specific scoring matrices (PSSMs).

Class I/II

16

MHCBench

Prediction comparison

Class I/II

17

ProPred

Quantitative matrices

Class II

18

Epipredict

Quantitative matrices

Class II

19

ProPred2

Promiscuous MHC class-II binding peptide prediction server

Class II

20

HLADR4Pred

SVM and ANN based HLA-DRB1*0401 binders prediction method

Class II

21

MHC2Pred

SVM based method for prediction of promiscuous MHC class II binders

Class II

22

MHC-Thread

Structure peptide threading

Class II

23

Indirect Links

Prediction method

Description

Type

References

NetChop

Neural network predictions for cleavage sites of the human proteasome

Human cleavage sites

1

PAProC

Prediction Algorithm for Proteasomal Cleavages

Proteasomal cleavages

2


Companies doing prediction for charge

 

last updated November 27, 2017; contacts: E-mail: kangueane@bioinformation.net; Phone: +91 9486267369

() Biomedical Informatics