A key step in the cellular adaptive immune response is the presentation of antigen to T cells . During this process short peptides processed from self or foreign proteins may be presented on the surface bound to MHC molecules for binding to T cell receptors . Those that bind and activate an immune response are called epitopes . Computational prediction of T cell epitopes has many applications in vaccine design and immuno-diagnostics . This is the basis of immunoinformatics which allows in silico screening of peptides before experiments are performed . The most effective approach is to estimate the binding affinity of a given peptide fragment to MHC class I or II molecules . With the availability of whole genomes for many microbial species it is now feasible to computationally screen whole proteomes for candidate peptides . epitopepredict is a programmatic framework and command line tool designed to aid this process . It provides access to multiple binding prediction algorithms under a single interface and scales for whole genomes using multiple target MHC alleles . A web interface is provided to assist visualization and filtering of the results . The software is freely available under an open source license from https: //github.com/dmnfarrell/epitopepredict