Strength in numbers: achieving greater accuracy in MHC-I binding prediction by combining the results from multiple prediction tools.

ABSTRACT:

Background

Peptides derived from endogenous antigens can bind to MHC class I molecules. Those which bind with high affinity can invoke a CD8+ immune response, resulting in the destruction of infected cells. Much work in immunoinformatics has involved the algorithmic prediction of peptide binding affinity to various MHC-I alleles. A number of tools for MHC-I binding prediction have been developed, many of which are available on the web.

Results

We hypothesize that peptides predicted by a number of tools are more likely to bind than those predicted by just one tool, and that the likelihood of a particular peptide being a binder is related to the number of tools that predict it, as well as the accuracy of those tools. To this end, we have built and tested a heuristic-based meth

SUBMITTER: Trost B 

PROVIDER: S-EPMC1847428 | biostudies-literature | 2007 Mar

REPOSITORIES: biostudies-literature