Webservers for Vaccinomics

This page provides information on softwares developed at raghava group for developing vaccine candidates.


Name Description
ABCpred Mapping of B-cell epitope(s) in an antigen sequence, using artificial neural network
AlgPred Prediction of allergenic proteins and mapping of IgE epitopes in antigens
BCEpred Prediction of linear B-cell epitopes, using Physico-chemical properties
BTXpred Prediction of bacterial toxins
CBtope Conformational B-cell Epitope prediction
HIVcoPred Prediction of coreceptor used by HIV-1 from Its V3 loop amino acid sequence
IFNEpitope Prediction and designing interferon-gamma inducing epitopes
IgPred Prediction of antibody specific B-cell epitope
IL-10pred Prediction of Interleukin-10 inducing peptides
IL4Pred In silico platform for designing and disovering of Interleukin-4 inducing peptides
ImRNA Prediction of immunomodulatory RNAs, for designing of vaccine adjuvants and non-toxic RNAs
LBtope Prediction of linear B-cell epitopes
mhc2pred SVM based method for prediction of promiscuous MHC class II binders
Pcleavage Identification of protesosomal cleavage sites in a protein sequence
propred Prediction of MHC Class-II binding regions in an antigen sequence
Propred1 Prediction of promiscuous MHC Class-I binders
TapPred Prediction of binding affinity of peptides toward the TAP transporter
Toxinpred Prediction and designing of toxic/non-toxic peptides
VaccineDA Prediction of oligodeoxynucleotide vaccine adjuvant
VaxinPAD Designing of peptide based vaccine adjuvant
cancer_pred Prediction of the cancerlectins
CancerCSP Gene expression-based biomarkers for discriminating early and late stage of clear cell renal cancer
cancerlsp Gene expression-based biomarkers and methylation data based discrimination of early and late stage of liver cancer
CancerSPP Prediction and analysis of primary and metastatic tumor of SKCM using signature genes expression data
CancerTSP Gene expression-based biomarkers for discriminating early and late stage of Papillary Thyroid Carcinoma
DesiRM Designing of highly efficient siRNA with minimum mutation approach
DipCell Designing of inhibitors against pancreatic cancer cell lines
Drugmint Identification of drug like molecules
ecgPred Analysis of expresion data and correlation between gene expression and nucleotides composition of genes
ntEGFR QSAR-Based Models for designing inhibitors against Wild and Mutant EGFR
PolyApred Prediction of polyadenylation signal (PAS) in human DNA sequence
RNAcon Prediction and classification of non-coding RNAs
RNAPin Prediction of Protein Interacting Nucleotides (PINs) in RNA sequences
SRF A program to find repeats through an analysis of the power spectrum of a given DNA sequence
tRNAMod Prediction of transfer RNA (tRNA) modifications
TumorHPD Prediction and designing of tumor homing peptides

About Raghava

Professor Gajendra P.S. Raghava, Indraprasta Institute of Information Technology, New Delhi is a strong supporter of open source software and open access, all resources developed at his group are free for scientific use.