Ontology highlight
ABSTRACT: Motivation
Microarray expression data reveal functionally associated proteins. However, most proteins that are associated are not actually in direct physical contact. Predicting physical interactions directly from microarrays is both a challenging and important task that we addressed by developing a novel machine learning method optimized for this task.Results
We validated our support vector machine-based method on several independent datasets. At the same levels of accuracy, our method recovered more experimentally observed physical interactions than a conventional correlation-based approach. Pairs predicted by our method to very likely interact were close in the overall network of interaction, suggesting our method as an aid for functional annotation. We applied the metho
SUBMITTER: Soong TT
PROVIDER: S-EPMC2579715 | biostudies-literature | 2008 Nov
REPOSITORIES: biostudies-literature