Analysis Tools for Detection and Diagnosis of Biological Threats

Award Information
Agency:
Department of Defense
Branch
Office for Chemical and Biological Defense
Amount:
$69,806.00
Award Year:
2004
Program:
SBIR
Phase:
Phase I
Contract:
DAMD17-04-C-0095
Award Id:
68692
Agency Tracking Number:
C041-113-0104
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
4700 Falls of Neuse, Suite 350, Raleigh, NC, 27609
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
HongDang
Senior Bioinformatician
(919) 954-0033
hdang@alpha-gamma.com
Business Contact:
ReeseHowle
President
(919) 954-0033
rhowle@alpha-gamma.com
Research Institute:
n/a
Abstract
DNA microarray technology, in combination with statistical and predictive modeling tools, could be used to evaluate thousands of genes against distinct gene expression patterns induced by chemical/biological agents to provide early identification and speed therapeutic intervention. The overall objective of this proposal is to demonstrate the feasibility of building a data management system for DNA microarray study data with integrated computational analysis tools that can provide identification of chemical and biological threats on the basis of host gene response. Alpha-Gamma proposes to accomplish these objectives by first building and populating a prototype relational database with several sets of DNA microarray data along with pathological and physiological endpoints. Alpha-Gamma will build a web-based user interface to browse and select data for analysis, and integrate established statistical tools (e.g., SAS, S-Plus, Spotfire, Patek) into this user friendly environment. With this integration of statistical tools, Alpha-Gamma will perform normalization of microarray data sets, cluster analysis, and pattern recognition. Alpha-Gamma will also validate the potential of this approach for identifying unknown agents by reserving known samples from the datasets and applying statistical tools to identify best match and confidence level.

* information listed above is at the time of submission.

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