Vaccinomics

Webservers and Databases related to Immunoinformatics

T-Helper Epitopes or MHC/HLA Class II binders 
(Adaptive Immunity, Exogenous Antigen)

MHCBN: A database of MHC-Binding, Non-binding peptides and T-cell epitopes.

ProPred: Identification of promiscuous MHC Class-II binding regions in an antigen sequence

HLA-DR4Pred: Identification of HLA-DRB1*0401(MHC class II alleles) binding peptides.

MHC: Matrix Optimization Technique for identification of binding core in MHC II binding peptides

MHC2Pred: The MHC4Pred is an SVM based method for prediction of promiscuous MHC class II binding peptides.

MHCBENCH: Benchmarking of MHC binding peptide prediction algorithms.

FDR4: Prediction of binding affinity of HLA-DRB*0401 binders in an antigenic sequence.

IL4pred: In silico platform for designing and disovering of interleukin-4 inducing peptides.

IFNepitope: Designing of interferon-gamma inducing epitopes.

CTL Epitopes or MHC/HLA Class I binders 
(Adaptive Immunity, Endogenous Antigens)

PROPRED1: Prediction of promiscuous binders for 47 MHC/HLA class I alleles using quantitative matrices;

Pcleavage: Identification of protesosomal cleavage sites in a protein sequence.

TAPpred: Prediction of TAP binding peptides for understanding of peptide internalization to endoplasmic reticulum.

CTLPred: A direct method for prediction of CTL epitopes.

nHLApred: This is a comprehensive method for prediction of MHC binding peptides or CTL epitopes of 67 MHC class I alleles.

MMBPred: Prediction of mutated MHC class I binders in an antigen, having high affinity and promiscuousity.

HLAPRED: The method can identify and predict HLA (both class I & II) binding regions in an antigen sequence.

Linear & Conformational B-cell Epitopes

BCIPEP: Collection & compilation of B-cell epitopes from literature

BCEPRED: Prediction of linear B-cell epitopes, using Physico-chemical properties

ABCPred: Mapping of B-cell epitope(s) in an antigen sequence, using artificial neural network.

CBTOPE: Conformational B cell prediction method: In the present study using amino acid composition as an input feature for Support vector machine (SVM).

LBTOPE: Advanced method for predicting linear B-cell epitopes (antigenic region) with high accuracy developed using recent data

IgPred: Identification of B-cell epitopes in an antigen for inducing specific class of antibodies

Innate Immunity & Misc. Servers

PRRDB: A comprehensive database of pattern-recogniton receptors and their ligands

VaxinPAD: Computer-aided designing of peptide-based vaccine adjuvants

VaccineDA: Prediction and designing DNA-based (Oligo-deoxy nucleotides) vaccine adjuvants.

imRNA: Prediction of immunomodulatory RNAs, for designing of vaccine adjuvants and non-toxic RNAs

ALGpred: A comprehensive database of pattern-recogniton receptors and their ligands

AntigenDB: This database provides information about a wide range of experimentally-validated antigens.

PolysacDB: A comprehensive database of microbial polysaccharide antigens and their antibodies

HAPTENDB: A database of haptens, provide comprehensive information about the hapten molecule

VaccineDA: Designing Vaccine Adjuvants based on immunomodulatory DNA.

MtbVeb: In silico platform for designing vaccine aginst mycobacterium tuberculosis.

CancerTope: In silico Platform for designing genome-based Personalized immunotherapy or Vaccine against Cancer.

AbAg: Compute the endpoint titer and concentration of Antibody(Ab) or Antigen(Ag) from ELISA data.