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The NamesforLife Semantic Index of Phenotypic and Genotypic Data for Systems Biology

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-FG02-11ER86493
Agency Tracking Number: 97372
Amount: $100,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: 34 b
Solicitation Number: DE-FOA-0000413
Solicitation Year: 2011
Award Year: 2011
Award Start Date (Proposal Award Date): 2011-06-17
Award End Date (Contract End Date): 2012-05-16
Small Business Information
333 Albert Ave Suite 202
East Lansing, MI 48823-4324
United States
DUNS: 786460449
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 George Garrity
 (517) 410-0525
Business Contact
 George Garrity
Title: Dr.
Phone: (517) 410-0525
Research Institution
 Michigan State University
2215 Biomedical & Physical Science
East Lansing, MI 48824-
United States

 () -
 Nonprofit College or University

The DOE Systems Biology Knowledgebase (Kbase) was envisioned to provide a framework to support modeling of dynamic cellular processes of microorganisms, plants and metacommunities. The Kbase will provide the tools and data to permit rapid iteration of experiments that draw on a variety of data types and allow endusers to infer how cells and communities respond to natural or induced perturbations, and ultimately to predict outcomes. The Systems Biology Knowledgebase Implementation Plan defines the needs and priorities for this initiative, which include biofuel production, bioremediation and carbon sequestration. Ultimately, the Kbase will provide a platform for accelerated acquisition of basic and applied biological knowledge. Predictive models depend on high quality input data. The authors of the Implementation Plan recognize that many different types of data are required to build such models. But not all data are of similar quality nor are all of the data amenable to computational analysis without extensive cleaning, interpretation and normalization. Key among those needed to make the Kbase fully operational arephenotypic data, which are more complex than sequence data, occur in a wide variety of forms, often use complex and nonuniform descriptors and are scattered about, principally in the scientific and technical literature or in specialized databases. Incorporating these data into the Kbase will require expertise in harvesting, modeling and interpreting the data. The NamesforLife Semantic Index of Phenotypic and Genotypic Data for Systems Biology seek to address this problem by taking the first steps toward ontology of phenotypes for Bacteria and Archaea, based on the taxonomic literature. Phase I of this project will create a draft vocabulary of phenotypic features that will enable integration of normalized phenotypic data into the Kbase in Phase II. This project builds on the N4L technology of NamesforLife, LLC.Commercial Applications and Other Benefits: The Companys data and applications bring enhanced accuracy and clarity of meaning to the life sciences and provide new methods of searching, indexing and abstracting scientific and technical literature

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