Baker, P.G., Brass, A., Bechhofer, S., Goble, C.A., Paton, N.W., and Stevens, R.. "TAMBIS--Transparent Access to Multiple Bioinformatics Information Sources." Proc Int Conf Intell Syst Mol Biol.
vol. 6.
1998.
pp. 25-34.
[ .pdf ] [ .ps ] [ PubMed ] [ WebSite ]
The TAMBIS project aims to provide transparent access to disparate biological databases and analysis tools, enabling users to utilize a wide range of resources with the minimum of effort. A prototype system has been developed that includes a knowledge base of biological terminology (the biological Concept Model), a model of the underlying data sources (the Source Model) and a 'knowledge-driven' user interface. Biological concepts are captured in the knowledge base using a description logic called GRAIL. The Concept Model provides the user with the concepts necessary to construct a wide range of multiple-source queries, and the user interface provides a flexible means of constructing and manipulating those queries. The Source Model provides a description of the underlying sources and mappings between terms used in the sources and terms in the biological Concept Model. The Concept Model and Source Model provide a level of indirection that shields the user from source details, providing a high level of source transparency. Source independent, declarative queries formed from terms in the Concept Model are transformed into a set of source dependent, executable procedures. Query formulation, translation and execution is demonstrated using a working example.
Keywords: Artificial Intelligence ; *Computational Biology ; Databases Factual ; User-Computer Interface
Baker, P.G., Goble, C.A., Bechhofer, S., Paton, N.W., Stevens, R., and Brass, A.. "An ontology for bioinformatics applications." Bioinformatics. 15
(6).
1999.
pp. 510-20.
[ .pdf ] [ .ps ] [ PubMed ] [ WebSite ]
MOTIVATION: An ontology of biological terminology provides a model of biological concepts that can be used to form a semantic framework for many data storage, retrieval and analysis tasks. Such a semantic framework could be used to underpin a range of important bioinformatics tasks, such as the querying of heterogeneous bioinformatics sources or the systematic annotation of experimental results. RESULTS: This paper provides an overview of an ontology [the Transparent Access to Multiple Biological Information Sources (TAMBIS) ontology or TaO] that describes a wide range of bioinformatics concepts. The present paper describes the mechanisms used for delivering the ontology and discusses the ontology's design and organization, which are crucial for maintaining the coherence of a large collection of concepts and their relationships. AVAILABILITY: The TAMBIS system, which uses a subset of the TaO described here, is accessible over the Web via http://img.cs.man.ac.uk/tambis (although in the first instance, we will use a password mechanism to limit the load on our server). The complete model is also available on the Web at the above URL.
Keywords: Classification ; *Computational Biology ; Databases Factual ; Expert Systems ; Models Biological
Hofestadt, R. and Thelen, S.. "Quantitative modeling of biochemical networks." In Silico Biol. 1
(1).
1998.
pp. 39-53.
[ PubMed ] [ WebSite ]
Today different database systems for molecular structures (genes and proteins) and metabolic pathways are available. All these systems are characterized by the static data representation. For progress in biotechnology the dynamic representation of this data is important. The metabolism can be characterized as a complex biochemical network. Different models for the quantitative simulation of biochemical networks are discussed, but no useful formalization is available. This paper shows that the theory of Petrinets is useful for the quantitative modeling of biochemical networks.
Keywords: *Biochemistry ; Biotechnology ; Catalysis ; Computational Biology ; *Computer Simulation ; Databases Factual ; Glycolysis ; Models Biological ; Protein Engineering
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
Karp, P.D.. "Pathway databases: a case study in computational symbolic theories." Science. 293
(5537).
2001.
pp. 2040-4.
[ .pdf ] [ PubMed ]
A pathway database (DB) is a DB that describes biochemical pathways, reactions, and enzymes. The EcoCyc pathway DB (see http://ecocyc.org) describes the metabolic, transport, and genetic-regulatory networks of Escherichia coli. EcoCyc is an example of a computational symbolic theory, which is a DB that structures a scientific theory within a formal ontology so that it is available for computational analysis. It is argued that by encoding scientific theories in symbolic form, we open new realms of analysis and understanding for theories that would otherwise be too large and complex for scientists to reason with effectively.
Keywords: Artificial Intelligence ; *Computational Biology ; Culture Media ; *Databases Factual ; Escherichia coli_enzymology ; Escherichia coli_*genetics ; Escherichia coli_growth and development ; Escherichia coli_*metabolism ; *Genome Bacterial ; Internet ; Software
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., and Kanehisa, M.. "KEGG: Kyoto Encyclopedia of Genes and Genomes." Nucleic Acids Res. 27
(1).
1999.
pp. 29-34.
[ .pdf ] [ PubMed ]
Kyoto Encyclopedia of Genes and Genomes (KEGG) is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules. The major component of KEGG is the PATHWAY database that consists of graphical diagrams of biochemical pathways including most of the known metabolic pathways and some of the known regulatory pathways. The pathway information is also represented by the ortholog group tables summarizing orthologous and paralogous gene groups among different organisms. KEGG maintains the GENES database for the gene catalogs of all organisms with complete genomes and selected organisms with partial genomes, which are continuously re-annotated, as well as the LIGAND database for chemical compounds and enzymes. Each gene catalog is associated with the graphical genome map for chromosomal locations that is represented by Java applet. In addition to the data collection efforts, KEGG develops and provides various computational tools, such as for reconstructing biochemical pathways from the complete genome sequence and for predicting gene regulatory networks from the gene expression profiles. The KEGG databases are daily updated and made freely available (http://www.genome.ad.jp/kegg/).
Keywords: Computational Biology ; *Databases Factual ; Gene Expression ; *Genes ; *Genome ; Ligands ; Metabolism ; Sequence Homology
Stevens, R., Baker, P.G., Bechhofer, S., Ng, G., Jacoby, A., Paton, N.W., Goble, C.A., and Brass, A.. "TAMBIS: transparent access to multiple bioinformatics information sources." Bioinformatics. 16
(2).
2000.
pp. 184-5.
[ PubMed ] [ WebSite ]
SUMMARY: TAMBIS (Transparent Access to Multiple Bioinformatics Information Sources) is an application that allows biologists to ask rich and complex questions over a range of bioinformatics resources. It is based on a model of the knowledge of the concepts and their relationships in molecular biology and bioinformatics. AVAILABILITY: TAMBIS is available as an applet from http://img.cs.man.ac.uk/tambis SUPPLEMENTARY: A full manual tutorial and videos can be found at http://img.cs.man.ac.uk/tambis. CONTACT: tambis
Keywords: Computational Biology ; *Information Storage and Retrieval ; *Software
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
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