Information-theoretic evaluation of predicted ontological annotations.

ABSTRACT:

Motivation

The development of effective methods for the prediction of ontological annotations is an important goal in computational biology, with protein function prediction and disease gene prioritization gaining wide recognition. Although various algorithms have been proposed for these tasks, evaluating their performance is difficult owing to problems caused both by the structure of biomedical ontologies and biased or incomplete experimental annotations of genes and gene products.

Results

We propose an information-theoretic framework to evaluate the performance of computational protein function prediction. We use a Bayesian network, structured according to the underlying ontology, to model the prior probability of a protein's function. We then define two concepts, misinfor

SUBMITTER: Clark WT 

PROVIDER: S-EPMC3694662 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature