Prediction of MHC class I binding peptides, using SVMHC.

ABSTRACT:

Background

T-cells are key players in regulating a specific immune response. Activation of cytotoxic T-cells requires recognition of specific peptides bound to Major Histocompatibility Complex (MHC) class I molecules. MHC-peptide complexes are potential tools for diagnosis and treatment of pathogens and cancer, as well as for the development of peptide vaccines. Only one in 100 to 200 potential binders actually binds to a certain MHC molecule, therefore a good prediction method for MHC class I binding peptides can reduce the number of candidate binders that need to be synthesized and tested.

Results

Here, we present a novel approach, SVMHC, based on support vector machines to predict the binding of peptides to MHC class I molecules. This method seems to perform slightly bett

SUBMITTER: Donnes P 

PROVIDER: S-EPMC129981 | biostudies-literature | 2002 Sep

REPOSITORIES: biostudies-literature