1. A computer implemented method that facilitates epitope prediction, comprising: training a logistic regression (LR) model for epitope prediction using information using a plurality of sources representative of standard and special features of a desired epitope, wherein the standard features comprise, alone or in conjunction, data representative of the identity and/or supertype of an major histocompatibility complex (MHC) allele, and data representative of the identity and/or chemical property of an amino acid at a certain position of an epitope, wherein the special features comprise, alone or Boolean combinations of, data representative of the standard features, the identity of an amino acid and/or the chemical property of the amino acid at a given position along either region that flanks an epitope and data representative of an amino acid and/or the chemical property of the amino acid at a given position along the MHC molecule.