Associate Provost for Research Boston University Medical Campus
NHGRI - National Human Genome Research Institute	Research Resources

Abstract

Abstract: The era of high-throughput genome sequencing has greatly increased the number of known protein sequences, but our knowledge of protein function has not kept pace; many newly discovered proteins are annotated as "function unknown". These genes, currently labeled as hypothetical, might support important biological cell functions and could potentially serve as important targets for medical, diagnostic, or pharmacological studies at the same time high-throughput functional genomics methods are generating data that shed light on protein functions, but it is difficult to integrate information from all of these sources in a comprehensive manner. We propose a systematic methodology for integration of multiple sources of gene function evidence based on probabilistic inference methods. We use a functional linkage graph representation of evidence, together with controlled vocabularies of function descriptors such as the GO ontology, and develop methods to integrate and propagate function classifications through evidence networks to generate predicted functions for proteins of unknown function, with probabilities to indicate the confidence of the prediction. We propose to design, develop validate and disseminate software for predicting protein functions using our methods, as well as making available a database of predictions that will be maintained current with the available evidence on an ongoing basis.

Thesaurus Terms:
bioinformatics, computer program /software, computer system design /evaluation, functional /structural genomics
protein sequence, protein structure function

Institution:	BOSTON UNIVERSITY
	881 COMMONWEALTH AVENUE
	BOSTON, MA 02215
Fiscal Year:	2006
Department:	BIOMEDICAL ENGINEERING
Project Start:	12-SEP-2005
Project End:	31-AUG-2008
ICD:	NATIONAL HUMAN GENOME RESEARCH INSTITUTE
IRG:	ZRG1