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.