Award details

From sequence to function: information retrieval and sematic networks as tools for improved function prediction

ReferenceBIO10507
Principal Investigator / Supervisor Professor Andy Brass
Co-Investigators /
Co-Supervisors
Professor Carole Goble
Institution The University of Manchester
DepartmentComputer Science
Funding typeResearch
Value (£) 136,212
StatusCompleted
TypeResearch Grant
Start date 01/07/1999
End date 01/07/2002
Duration36 months

Abstract

Prediction of protein function from sequence is a key task in Bioinformatics but is a difficult process to automate efficiently. In this project automated tools for sequence analysis will be produced. The results from this analysis will then be subject to analysis from information retrieval theory to produce a set of index terms. These terms will be used to determine the relatedness of the information generated and assist in the process of function prediction. Description logics will then be used to generate an intelligent thesaurus for a model biological domain which can be used to link index terms to concepts. This information will be used to generate automated function prediction based on biological knowledge.

Summary

unavailable
Committee Not funded via Committee
Research TopicsX – not assigned to a current Research Topic
Research PriorityX – Research Priority information not available
Research Initiative Bioinformatics (Phase 2) (BIO) [1998-2000]
Funding SchemeX – not Funded via a specific Funding Scheme
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