On evaluating MHC-II binding peptide prediction methods.

ABSTRACT: Choice of one method over another for MHC-II binding peptide prediction is typically based on published reports of their estimated performance on standard benchmark datasets. We show that several standard benchmark datasets of unique peptides used in such studies contain a substantial number of peptides that share a high degree of sequence identity with one or more other peptide sequences in the same dataset. Thus, in a standard cross-validation setup, the test set and the training set are likely to contain sequences that share a high degree of sequence identity with each other, leading to overly optimistic estimates of performance. Hence, to more rigorously assess the relative performance of different prediction methods, we explore the use of similarity-reduced datasets. We introduce thre

SUBMITTER: El-Manzalawy Y 

PROVIDER: S-EPMC2533399 | biostudies-literature | 2008 Sep

REPOSITORIES: biostudies-literature