|
|
Modeling
Metabolic Pathways: A Bioinformatics Approach
Imran Shah
University of Colorado
The overall goal of this project is to develop novel
bioinformatics tools to aid metabolic engineering (ME). The
final final product this project is a predictive computational
system for metabolic pathway elucidation utilizing
high-throughput biomolecular data (mostly genomic sequence and
expression), background biological knowledge and novel inference
techniques. To achieve this goal we are developing
bioinformatics software to address the following challenges: (i)
biochemical data representation and integration from public
domain sources, which is necessary to effectively compute with
biomolecular information; (ii) the accurate assignment of
biocatalytic function to protein sequences using machine
learning methods, which is necessary to place putative proteins
in a biochemical context, and (iii) the elucidation of pathways
by heuristic search, which is necessary to automatically relate
sets of putative enzymes in a broader metabolic context. When
implemented the system will be made available to the ME
community through interactive web-accessible software. We are
approaching the problem in a general manner so that the system
will be useful in annotating whole microbial genomes, in finding
alternative routes in a partially complete pathways, or even
elucidating pathways that have not been observed before.
Return to Table of
Contents
|
|
