Bibliography of: Enzymes_genetics

  1. Ellis, L.B., Hershberger, C.D., Bryan, E.M., and Wackett, L.P.. "The University of Minnesota Biocatalysis/Biodegradation Database: emphasizing enzymes." Nucleic Acids Res. 29 (1). 2001. pp. 340-3.
    [ .pdf ] [ PubMed ]

    The University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD, http://umbbd.ahc.umn.edu/) provides curated information on microbial catabolic enzymes and their organization into metabolic pathways. Currently, it contains information on over 400 enzymes. In the last year the enzyme page was enhanced to contain more internal and external links; it also displays the different metabolic pathways in which each enzyme participates. In collaboration with the Nomenclature Commission of the International Union of Biochemistry and Molecular Biology, 35 UM-BBD enzymes were assigned complete EC codes during 2000. Bacterial oxygenases are heavily represented in the UM-BBD; they are known to have broad substrate specificity. A compilation of known reactions of naphthalene and toluene dioxygenases were recently added to the UM-BBD; 73 and 108 were listed respectively. In 2000 the UM-BBD is mirrored by two prestigious groups: the European Bioinformatics Institute and KEGG (the Kyoto Encyclopedia of Genes and Genomes). Collaborations with other groups are being developed. The increased emphasis on UM-BBD enzymes is important for predicting novel metabolic pathways that might exist in nature or could be engineered. It also is important for current efforts in microbial genome annotation.

    Keywords: Bacteria_genetics ; Bacteria_metabolism ; Biodegradation ; Catalysis ; *Databases Factual ; Enzymes_genetics ; Enzymes_*metabolism ; Fungi_genetics ; Fungi_metabolism ; Information Storage and Retrieval ; Internet


  2. Ellis, L.B., Hershberger, C.D., and Wackett, L.P.. "The University of Minnesota Biocatalysis/Biodegradation Database: specialized metabolism for functional genomics." Nucleic Acids Res. 27 (1). 1999. pp. 373-6.
    [ .pdf ] [ PubMed ]

    The University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD, http://www.labmed.umn.edu/umbbd/i nde x.html) first became available on the web in 1995 to provide information on microbial biocatalytic reactions of, and biodegradation pathways for, organic chemical compounds, especially those produced by man. Its goal is to become a representative database of biodegradation, spanning the diversity of known microbial metabolic routes, organic functional groups, and environmental conditions under which biodegradation occurs. The database can be used to enhance understanding of basic biochemistry, biocatalysis leading to speciality chemical manufacture, and biodegradation of environmental pollutants. It is also a resource for functional genomics, since it contains information on enzymes and genes involved in specialized metabolism not found in intermediary metabolism databases, and thus can assist in assigning functions to genes homologous to such less common genes. With information on >400 reactions and compounds, it is poised to become a resource for prediction of microbial biodegradation pathways for compounds it does not contain, a process complementary to predicting the functions of new classes of microbial genes.

    Keywords: Bacteria_genetics ; Bacteria_*metabolism ; Bacterial Proteins_metabolism ; *Biodegradation ; Biotechnology ; *Catalysis ; *Databases Factual_trends ; Environmental Pollution ; Enzymes_chemistry ; Enzymes_genetics ; Enzymes_metabolism ; Genes ; Bacterial_genetics ; Genes ; Bacterial_physiology ; Human ; Information Storage and Retrieval ; Internet ; Minnesota ; Universities


  3. Karp, P.D., Riley, M., Paley, S.M., Pellegrini-Toole, A., and Krummenacker, M.. "Eco Cyc: encyclopedia of Escherichia coli genes and metabolism." Nucleic Acids Res. 27 (1). 1999. pp. 55-8.
    [ .pdf ] [ PubMed ]

    The EcoCyc database describes the genome and gene products of Escherichia coli, its metabolic and signal-transduction pathways, and its tRNAs. The database describes 4391 genes of E.coli, 695 enzymes encoded by a subset of these genes, 904 metabolic reactions that occur in E.coli, and the organization of these reactions into 129 metabolic pathways. The EcoCyc graphical user interface allows scientists to query and explore the EcoCyc database using visualization tools such as genomic-map browsers and automatic layouts of metabolic pathways. EcoCyc has many references to the primary literature, and is a (qualitative) computational model of E. coli metabolism. EcoCyc is available at URL http://ecocyc. PangeaSystems.com/ecocyc/

    Keywords: Classification ; *Databases Factual ; Enzymes_genetics ; Enzymes_metabolism ; Escherichia coli_*genetics ; Escherichia coli_*metabolism ; *Genes Bacterial ; Genome Bacterial ; Information Storage and Retrieval ; Internet ; Signal Transduction ; User-Computer Interface


  4. Kuffner, R., Zimmer, R., and Lengauer, T.. "Pathway analysis in metabolic databases via differential metabolic display (DMD)." Bioinformatics. 16 (9). 2000. pp. 825-36.
    [ .pdf ] [ PubMed ] [ WebSite ]

    MOTIVATION: A number of metabolic databases are available electronically, some with features for querying and visualizing metabolic pathways and regulatory networks. We present a unifying, systematic approach based on PETRI nets for storing, displaying, comparing, searching and simulating such nets from a number of different sources. RESULTS: Information from each data source is extracted and compiled into a PETRI net. Such PETRI nets then allow to investigate the (differential) content in metabolic databases, to map and integrate genomic information and functional annotations, to compare sequence and metabolic databases with respect to their functional annotations, and to define, generate and search paths and pathways in nets. We present an algorithm to systematically generate all pathways satisfying additional constraints in such PETRI nets. Finally, based on the set of valid pathways, so-called differential metabolic displays (DMDs) are introduced to exhibit specific differences between biological systems, i.e. different developmental states, disease states, or different organisms, on the level of paths and pathways. DMDs will be useful for target finding and function prediction, especially in the context of the interpretation of expression data.

    Keywords: *Algorithms ; Catalysis ; Computational Biology_*methods ; Computer Simulation ; *Data Display ; *Databases Factual ; Enzymes_genetics ; Enzymes_metabolism ; Glycolysis ; Metabolism_*physiology ; Mycoplasma_metabolism ; Yeasts_metabolism