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Toxin Knowledge Base:
A System for Discovering Bioengineered Threats by Knowledge Base Driven
Mining of Toxin Data
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Team
Hasan Davulcu
Vish Ramachandran
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Abstract
The
overall goal of this work is to establish a Toxin Knowledge Base – a
bioinformatics resource primarily focused on molecular information about
toxins and other virulence factors that are the natural products of
biological and potential biological warfare agents. The resource will be mined to
assimilate, synthesize, analyze and disseminate genomic and structural
information on genes of these agents and their products. Advances in
recombinant DNA technology
have opened up possibilities for production of bioengineered pathogens or
their products on scales that could make them formidable weapons of
bioterrorism. Chimeric
molecules form another kind of threat wherein the virulent domain of a
toxin is hidden in what is otherwise a non-pathogenic protein. In this project we propose to
collect all relevant information pertaining to toxins at molecular level
and expand the existing Toxin
Knowledge Base to identify potential virulence factors. Using advanced machine learning and
data mining we will mine the database to look for motifs, to design new
experiments and also to predict structure and function of molecules
(including putative chimeras) for which these data are not available. Knowledge learned from this and similar
analysis will be encoded as rules in an expert system. Both the database and its front-end
expert system will be used for analyzing genomic data to identify specific
regions that encode factors that contribute to virulence.
Dr.
Hasan Davulcu was awarded a joint research grant, funded by the U.S. Army
Medical Research Institute of Infectious Disease and Department of Defense.
The grant will be used to establish the Toxin Knowledge Base, a resource
that will help in the fight against bioterrorism.
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