Bibliography of Year: 2002

  1. Kanehisa, M., Goto, S., Kawashima, S., and Nakaya, A.. "The KEGG databases at GenomeNet." Nucleic Acids Res. 30 (1). 2002. pp. 42-6.
    [ .pdf ] [ PubMed ]

    The Kyoto Encyclopedia of Genes and Genomes (KEGG) is the primary database resource of the Japanese GenomeNet service (http://www.genome.ad.jp/) for understanding higher order functional meanings and utilities of the cell or the organism from its genome information. KEGG consists of the PATHWAY database for the computerized knowledge on molecular interaction networks such as pathways and complexes, the GENES database for the information about genes and proteins generated by genome sequencing projects, and the LIGAND database for the information about chemical compounds and chemical reactions that are relevant to cellular processes. In addition to these three main databases, limited amounts of experimental data for microarray gene expression profiles and yeast two-hybrid systems are stored in the EXPRESSION and BRITE databases, respectively. Furthermore, a new database, named SSDB, is available for exploring the universe of all protein coding genes in the complete genomes and for identifying functional links and ortholog groups. The data objects in the KEGG databases are all represented as graphs and various computational methods are developed to detect graph features that can be related to biological functions. For example, the correlated clusters are graph similarities which can be used to predict a set of genes coding for a pathway or a complex, as summarized in the ortholog group tables, and the cliques in the SSDB graph are used to annotate genes. The KEGG databases are updated daily and made freely available (http://www.genome.ad.jp/kegg/).

    Keywords: Computational Biology ; Computer Graphics ; *Databases Genetic ; *Databases Protein ; Gene Expression Profiling ; *Genome ; Human ; Information Storage and Retrieval ; Internet ; Macromolecular Systems ; Metabolism_genetics ; Multigene Family ; Protein Conformation ; Proteins_chemistry ; Proteins_genetics ; Proteins_metabolism ; Sequence Homology


  2. Kawashima, T., Kawashima, S., Kohara, Y., Kanehisa, M., and Makabe, K.W.. "Update of MAGEST: Maboya Gene Expression patterns and Sequence Tags." Nucleic Acids Res. 30 (1). 2002. pp. 119-20.
    [ .pdf ] [ PubMed ]

    MAGEST is a database for maternal gene expression information for an ascidian, Halocynthia roretzi. The ascidian has become an animal model in developmental biological research because it shows a simple developmental process, and belongs to one of the chordate groups. Various data are deposited into the MAGEST database, e.g. the 3'- and 5'-tag sequences from the fertilized egg cDNA library, the results of similarity searches against GenBank and the expression data from whole mount in situ hybridization. Over the last 2 years, the data retrieval systems have been improved in several aspects, and the tag sequence entries have increased to over 20 000 clones. Additionally, we constructed a database, translated MAGEST, for the amino acid fragment sequences predicted from the EST data sets. Using this information comprehensively, we should obtain new information on gene functions. The MAGEST database is accessible via the Internet at http://www.genome.ad.jp/magest/.

    Keywords: Amino Acid Sequence ; DNA Complementary_genetics ; *Databases Genetic ; *Expressed Sequence Tags ; Forecasting ; *Gene Expression Regulation ; Developmental ; Gene Library ; In Situ Hybridization ; Information Storage and Retrieval ; Internet ; RNA Messenger Stored_biosynthesis ; Urochordata_*embryology ; Urochordata_*genetics ; Urochordata_metabolism ; Zygote_metabolism


  3. Karp, P.D., Paley, S.M., and Romero, P.. "The Pathway Tools software." Bioinformatics. vol. 18 Suppl 1. 2002. pp. S225-32.
    [ .pdf ] [ PubMed ] [ WebSite ]

    Motivation: Bioinformatics requires reusable software tools for creating model-organism databases (MODs). Results: The Pathway Tools is a reusable production-quality software environment for creating a type of MOD called a Pathway/Genome Database (PGDB). A PGDB such as EcoCyc (see http://ecocyc.org) integrates our evolving understanding of the genes, proteins, metabolic network, and genetic network of an organism. This paper provides an overview of the four main components of the Pathway Tools: The PathoLogic component supports creation of new PGDBs from the annotated genome of an organism. The Pathway/Genome Navigator provides query, visualization, and Web-publishing services for PGDBs. The Pathway/Genome Editors support interactive updating of PGDBs. The Pathway Tools ontology defines the schema of PGDBs. The Pathway Tools makes use of the Ocelot object database system for data management services for PGDBs. The Pathway Tools has been used to build PGDBs for 13 organisms within SRI and by external users. Availability: The software is freely available to academics and is available for a fee to commercial institutions. Contact ptools-support


  4. Karp, P.D., Riley, M., Paley, S.M., and Pellegrini-Toole, A.. "The MetaCyc Database." Nucleic Acids Res. 30 (1). 2002. pp. 59-61.
    [ .pdf ] [ PubMed ]

    MetaCyc is a metabolic-pathway database that describes 445 pathways and 1115 enzymes occurring in 158 organisms. MetaCyc is a review-level database in that a given entry in MetaCyc often integrates information from multiple literature sources. The pathways in MetaCyc were determined experimentally and are labeled with the species in which they are known to occur based on literature references examined to date. MetaCyc contains extensive commentary and literature citations. Applications of MetaCyc include pathway analysis of genomes, metabolic engineering and biochemistry education. MetaCyc is queried using the Pathway Tools graphical user interface, which provides a wide variety of query operations and visualization tools. MetaCyc is available via the World Wide Web at http://ecocyc.org/ecocyc/metacyc.html, and is available for local installation as a binary program for the PC and the Sun workstation, and as a set of flatfiles. Contact metacyc-info

    Keywords: Comparative Study ; Database Management Systems ; *Databases Protein ; Enzymes_chemistry ; Enzymes_*metabolism ; Genome ; Human ; Information Storage and Retrieval ; Internet ; *Metabolism


  5. Karp, P.D., Riley, M., Saier, M., Paulsen, I.T., Collado-Vides, J., Paley, S.M., Pellegrini-Toole, A., Bonavides, C., and Gama-Castro, S.. "The EcoCyc Database." Nucleic Acids Res. 30 (1). 2002. pp. 56-8.
    [ .pdf ] [ PubMed ]

    EcoCyc is an organism-specific pathway/genome database that describes the metabolic and signal-transduction pathways of Escherichia coli, its enzymes, its transport proteins and its mechanisms of transcriptional control of gene expression. EcoCyc is queried using the Pathway Tools graphical user interface, which provides a wide variety of query operations and visualization tools. EcoCyc is available at http://ecocyc.org/.

    Keywords: Database Management Systems ; *Databases Genetic ; Escherichia coli_*genetics ; Escherichia coli_*metabolism ; Escherichia coli Proteins_*genetics ; Escherichia coli Proteins_*physiology ; Gene Expression Regulation Bacterial ; *Genome Bacterial ; Information Storage and Retrieval ; Internet ; Protein Transport ; Signal Transduction


  6. Ma, L. and Iglesias, P.A.. "Quantifying robustness of biochemical network models." BMC Bioinformatics. 3 (1). 2002. pp. 38.
    [ .pdf ] [ PubMed ] [ WebSite ]

    BACKGROUND: Robustness of mathematical models of biochemical networks is important for validation purposes and can be used as a means of selecting between different competing models. Tools for quantifying parametric robustness are needed. RESULTS: Two techniques for describing quantitatively the robustness of an oscillatory model were presented and contrasted. Single-parameter bifurcation analysis was used to evaluate the stability robustness of the limit cycle oscillation as well as the frequency and amplitude of oscillations. A tool from control engineering - the structural singular value (SSV) - was used to quantify robust stability of the limit cycle. Using SSV analysis, we find very poor robustness when the model's parameters are allowed to vary. CONCLUSION: The results show the usefulness of incorporating SSV analysis to single parameter sensitivity analysis to quantify robustness.


  7. Peleg, M., Yeh, I., and Altman, R.B.. "Modelling biological processes using workflow and Petri Net models." Bioinformatics. 18 (6). 2002. pp. 825-37.
    [ .pdf ] [ PubMed ] [ WebSite ]

    MOTIVATION: Biological processes can be considered at many levels of detail, ranging from atomic mechanism to general processes such as cell division, cell adhesion or cell invasion. The experimental study of protein function and gene regulation typically provides information at many levels. The representation of hierarchical process knowledge in biology is therefore a major challenge for bioinformatics. To represent high-level processes in the context of their component functions, we have developed a graphical knowledge model for biological processes that supports methods for qualitative reasoning. RESULTS: We assessed eleven diverse models that were developed in the fields of software engineering, business, and biology, to evaluate their suitability for representing and simulating biological processes. Based on this assessment, we combined the best aspects of two models: Workflow/Petri Net and a biological concept model. The Workflow model can represent nesting and ordering of processes, the structural components that participate in the processes, and the roles that they play. It also maps to Petri Nets, which allow verification of formal properties and qualitative simulation. The biological concept model, TAMBIS, provides a framework for describing biological entities that can be mapped to the workflow model. We tested our model by representing malaria parasites invading host erythrocytes, and composed queries, in five general classes, to discover relationships among processes and structural components. We used reachability analysis to answer queries about the dynamic aspects of the model. AVAILABILITY: The model is available at http://smi.stanford.edu/projects/helix/pubs/process-model/.


  8. Stelling, J., Klamt, S., Bettenbrock, K., Schuster, S., and Gilles, E.D.. "Metabolic network structure determines key aspects of functionality and regulation." Nature. 420 (6912). 2002. pp. 190-3.
    [ .pdf ] [ PubMed ]

    The relationship between structure, function and regulation in complex cellular networks is a still largely open question. Systems biology aims to explain this relationship by combining experimental and theoretical approaches. Current theories have various strengths and shortcomings in providing an integrated, predictive description of cellular networks. Specifically, dynamic mathematical modelling of large-scale networks meets difficulties because the necessary mechanistic detail and kinetic parameters are rarely available. In contrast, structure-oriented analyses only require network topology, which is well known in many cases. Previous approaches of this type focus on network robustness or metabolic phenotype, but do not give predictions on cellular regulation. Here, we devise a theoretical method for simultaneously predicting key aspects of network functionality, robustness and gene regulation from network structure alone. This is achieved by determining and analysing the non-decomposable pathways able to operate coherently at steady state (elementary flux modes). We use the example of Escherichia coli central metabolism to illustrate the method.

    Keywords: Biomass ; Cell Physiology ; Computational Biology ; Computer Simulation ; *Energy Metabolism ; Escherichia coli_genetics ; Escherichia coli_growth and development ; Escherichia coli_*metabolism ; Gene Expression Regulation Bacterial ; *Models Biological ; Phenotype ; Systems Theory


  9. Steffen, M., Petti, A., Aach, J., D'haeseleer, P., and Church, G.. "Automated modelling of signal transduction networks." BMC Bioinformatics. 3 (1). 2002. pp. 34.
    [ .pdf ] [ PubMed ] [ WebSite ]

    BACKGROUND: Intracellular signal transduction is achieved by networks of proteins and small molecules that transmit information from the cell surface to the nucleus, where they ultimately effect transcriptional changes. Understanding the mechanisms cells use to accomplish this important process requires a detailed molecular description of the networks involved. RESULTS: We have developed a computational approach for generating static models of signal transduction networks which utilizes protein-interaction maps generated from large-scale two-hybrid screens and expression profiles from DNA microarrays. Networks are determined entirely by integrating protein-protein interaction data with microarray expression data, without prior knowledge of any pathway intermediates. In effect, this is equivalent to extracting subnetworks of the protein interaction dataset whose members have the most correlated expression profiles. CONCLUSION: We show that our technique accurately reconstructs MAP Kinase signaling networks in Saccharomyces cerevisiae. This approach should enhance our ability to model signaling networks and to discover new components of known networks. More generally, it provides a method for synthesizing molecular data, either individual transcript abundance measurements or pairwise protein interactions, into higher level structures, such as pathways and networks.


  10. Schuster, S., Pfeiffer, T., Moldenhauer, F., Koch, I., and Dandekar, T.. "Exploring the pathway structure of metabolism: decomposition into subnetworks and application to Mycoplasma pneumoniae." Bioinformatics. 18 (2). 2002. pp. 351-61.
    [ PubMed ] [ WebSite ]

    MOTIVATION: Reconstructing and analyzing the metabolic map of microorganisms is an important challenge in bioinformatics. Pathway analysis of large metabolic networks meets with the problem of combinatorial explosion of pathways. Therefore, appropriate algorithms for an automated decomposition of these networks into smaller subsystems are needed. RESULTS: A decomposition algorithm for metabolic networks based on the local connectivity of metabolites is presented. Interrelations of this algorithm with alternative methods proposed in the literature and the theory of small world networks are discussed. The applicability of our method is illustrated by an analysis of the metabolism of Mycoplasma pneumoniae, which is an organism of considerable medical interest. The decomposition gives rise to 19 subnetworks. Three of these are here discussed in biochemical terms: arginine degradation, the tetrahydrofolate system, and nucleotide metabolism. The interrelations of pathway analysis of biochemical networks with Petri net theory are outlined.

    Keywords: Algorithms ; Arginine_metabolism ; Computational Biology ; *Metabolism ; Models Biological ; Mycoplasma pneumoniae_*metabolism ; Nucleotides_metabolism ; *Software