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Phenotyping All Genes of S. cerevisiae

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R41GM074543-01A1
Agency Tracking Number: GM074543
Amount: $123,238.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Timeline
Solicitation Year: N/A
Award Year: 2004
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
BIOLOG, INC. 3938 TRUST WAY
HAYWARD, CA 94545
United States
DUNS: N/A
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 MICHAEL ZIMAN
 (510) 785-2564
 MZIMAN@BIOLOG.COM
Business Contact
 BARRY BOCHNER
Phone: (510) 785-2564
Email: BBOCHNER@BIOLOG.COM
Research Institution
N/A
Abstract

DESCRIPTION (provided by applicant): The objective of this project is to further develop, miniaturize, and extend the new Phenotype MicroArray (PM) platform technology (1-3) and then utilize this improved technology to genomically analyze biological pathways and gene function in the model eucaryotic microorganism Saccharomyces cerevisiae. The steps will be 1) development of miniaturized, more efficient, and lower cost second generation technology, 2) characterization of all of S. cerevisiae's known genes, 3) construction of a computerized, database integrating this genomic and phenotypic information, and 4) retrospective evaluation and modifications of PM technology to make it more useful and comprehensive. Phase I will primarily be concerned with step 1 of this process.

A major need in current research is to understand, in depth, the function of large numbers of genes. Multiple, independent approaches are needed. Biolog's new PM technology provides a new approach in which one gene at a time is tested by phenotypic assay under thousands of cellular conditions. Testing of large numbers of genes is accomplished by testing a comprehensive collection of isogenic microbial strains with single gene knockouts or other alterations in an automated high-throughput program. With this approach, we can rapidly and efficiently build up a storehouse of information about gene function that will be extremely valuable to biological researchers.

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

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