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CG-GRID: Computational Genetics Grid Resource for Interaction Discovery

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 2R42GM097765-03
Agency Tracking Number: R42GM097765
Amount: $2,209,644.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: 400
Solicitation Number: PAR09-221
Timeline
Solicitation Year: 2016
Award Year: 2014
Award Start Date (Proposal Award Date): 2014-06-02
Award End Date (Contract End Date): 2017-04-30
Small Business Information
11260 ROGER BACON DR
Reston, VA 20190-5227
United States
DUNS: 158679253
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 JASON MOORE
 (215) 573-4411
 jhmoore@upenn.edu
Business Contact
 PAULA GAWTHORPARMENTROUT
Phone: (703) 689-9689
Email: parmentrout@parabon.com
Research Institution
 DARTMOUTH COLLEGE
 
11 ROPE FERRY RD. #6210
HANOVER, NH 03755-1421
United States

 Nonprofit College or University
Abstract

DESCRIPTION provided by applicant Advances in DNA sequencing technology have now made it practical and affordable to generate datasets containing millions of genetic attributes that can be tested for association with disease susceptibility The computational complexity of searching for genetic interactions over such high dimensional datasets imposes great challenges for genome wide association studies GWAS In Phase I of this project the Parabon research team led by principal investigator Dr Jason Moore of Dartmouth College Geisel School of Medicine began addressing these bottlenecks by developing a distributed software service for analyzing gene gene interactions over large GWAS datasets In particular the multifactor dimensionality reduction MDR algorithm was adapted for use in the Parabon R Crushandquot genome mining application MDR was augmented to employ Crushandapos s opportunistic evolution search algorithm to enable deep cloud powered search across thousands of compute nodes to identify complex patterns of gene gene interaction associated with human disease endpoints or forensically relevant traits The resultant Crush MDR Software as a Service SaaS application which is available as an online andquot cloudandquot service or in house enterprise application was validated and shown to have excellent performance characteristics using simulated GWAS data and then used to analyze a dataset from the Alzheimerandapos s Disease Neuroimaging Initiative In Phase II the Parabon development team will extend the analytical capabilities of the Crush MDR service and address other GWAS and next generation sequencing NGS bottlenecks by enhancing its Parabon R Frontier R Compute Platform a commercial cloud computing platform designed for high performance computing HPC applications Our overall objective which was derived from interactions with prospective customers is to produce a Platform as a Service PaaS solution that will greatly accelerate bioinformatics research by providing a comprehensive set of cloud services that collectively address many common bioinformatics bottlenecks and barriers to collaboration PUBLIC HEALTH RELEVANCE There is tremendous opportunity to identify new genetic risk factors for common human diseases given the availability of powerful new DNA sequencing technology We have established a novel software platform that can offer users the ability to identify combinations of genetic risk factors using high performance computing as an online service We will extend this software platform in new and novel ways and introduce it to the industrial and academic communities as a commercial product

* Information listed above is at the time of submission. *

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