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Minnesota Supercomputing Institute


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Research Abstracts Online
January 2008 - March 2009

University of Minnesota Twin Cities
Medical School
Department of Laboratory Medicine and Pathology

PI: Lynda B. M. Ellis, Associate Fellow

Databases for Microbes and Men

These researchers have developed several databases and tools that are housed in the SDML. The University of Minnesota Biocatalysis and Biodegradation Database (UM-BBD, umbbd.msi.umn.edu/) contains information on microbial biocatalytic reactions and biodegradation pathways for primarily xenobiotic, chemical compounds. The goal of the UM-BBD is to provide information on microbial enzyme-catalyzed reactions that are important for biotechnology. Its Pathway Prediction System (PPS, umbbd.msi.umn.edu /predict/) predicts microbial catabolic reactions using substructure searching, a rule-base, and atom-to-atom mapping. The system can recognize organic functional groups found in a compound and predict transformations based on biotransformation rules. The biotransformation rules are based on reactions found in the UM-BBD or in the scientific literature. The Vertebrate Secretome Database (VSDB, www.secretomes.umn.edu/) processes RefSeq vertebrate proteins through a sequence analysis pipeline. The resulting reference database can be compared to user-supplied sequences and the entire database or subsets can be downloaded.

Group Members

Kathrin Fenner, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
Jeff Gao, Graduate Student
Carol Gross, Staff
Getiria Onsongo, Graduate Student
Carlos Sosa, Research Associate
Michael Turnbull, Staff