Bibliography of: Models Biological

  1. 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


  2. Hofestadt, R., Mavrovouniotis, M.L., Collado-Vides, J., and Loffler, M.. "Modeling and simulation of metabolic pathways, gene regulation and cell differentiation. October 22-27, 1995. International Conference and Research Center for Computer Science, Schloss Dagstuhl, Saarland, Germany." Bioessays. 18 (4). 1996. pp. 333-5.
    [ PubMed ]

    Keywords: Cell Differentiation ; *Computer Simulation ; Gene Expression Regulation ; Information Systems ; Metabolism ; *Models Biological


  3. 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


  4. Hofestadt, R.. "Grammatical formalization of metabolic processes." Proc Int Conf Intell Syst Mol Biol. vol. 1. 1993. pp. 181-9.
    [ PubMed ]

    In the field of biotechnology and medicine it is of interest to model and simulate metabolic processes. The usual methods to model metabolic pathways are chemical descriptions and differential equations. Moreover, the graph theoretical aspect is discussed and the development of expert systems is in process. In this paper we present the formalization of metabolic processes. Our formalization is based on the theory of formal languages. This formalization is called genetic grammar and represents an expansion of the Semi-Thue-System.

    Keywords: *Computer Simulation ; *Expert Systems ; Gene Expression ; *Metabolism ; *Models Biological ; Programming Languages


  5. Mavrovouniotis, M.L.. "Identification of localized and distributed bottlenecks in metabolic pathways." Proc Int Conf Intell Syst Mol Biol. vol. 1. 1993. pp. 275-83.
    [ PubMed ]

    The usual thermodynamic evaluation, based solely on the Standard Gibbs Energy of reaction, does not take into account the permissible ranges of concentrations of metabolites, and it faces further difficulties when, instead of isolated reactions, we are examining whole pathways. For pathways, we seek not only to decide whether they are feasible but also to pinpoint the pathway segment that causes any thermodynamic difficulties. We define a set of scaled quantities which reformulate the thermodynamic-feasibility problem for the whole pathway. We present an algorithm which analyzes individual reactions and selective construction of larger subpathways and uncovers localized and distributed thermodynamic bottlenecks of the biotransformation. This type of thermodynamic treatment contributes to the effort to include more physical, chemical, and biological factors in the computer-aided analysis of metabolic pathways.

    Keywords: *Algorithms ; *Computer Simulation ; Glycolysis ; *Metabolism ; *Models Biological ; *Thermodynamics


  6. Oliveira, J.S., Bailey, C.G., Jones-Oliveira, J.B., and Dixon, D.A.. "An algebraic-combinatorial model for the identification and mapping of biochemical pathways." Bull Math Biol. 63 (6). 2001. pp. 1163-96.
    [ .pdf ] [ PubMed ]

    We develop the mathematical machinery for the construction of an algebraic-combinatorial model using Petri nets to construct an oriented matroid representation of biochemical pathways. For demonstration purposes, we use a model metabolic pathway example from the literature to derive a general biochemical reaction network model. The biomolecular networks define a connectivity matrix that identifies a linear representation of a Petri net. The sub-circuits that span a reaction network are subject to flux conservation laws. The conservation laws correspond to algebraic-combinatorial dual invariants, that are called S- (state) and T- (transition) invariants. Each invariant has an associated minimum support. We show that every minimum support of a Petri net invariant defines a unique signed sub-circuit representation. We prove that the family of signed sub-circuits has an implicit order that defines an oriented matroid. The oriented matroid is then used to identify the feasible sub-circuit pathways that span the biochemical network as the positive cycles in a hyper-digraph.

    Keywords: Linear Models ; Mathematical Computing ; *Models Biological ; *Models Chemical


  7. Reddy, V.N., Mavrovouniotis, M.L., and Liebman, M.N.. "Petri net representations in metabolic pathways." Proc Int Conf Intell Syst Mol Biol. vol. 1. 1993. pp. 328-36.
    [ PubMed ]

    The present methods for representing metabolic pathways are limited in their ability to handle complex systems, incorporate new information, and to provide for drawing qualitative conclusions from the structure of pathways. The theory of Petri nets is introduced as a tool for computer-implementable representation of pathways. Petri nets have the potential to overcome the present limitations, and through a multitude of properties, enable the preliminary qualitative analysis of pathways.

    Keywords: *Computer Simulation ; Fructose_metabolism ; Liver_metabolism ; *Metabolism ; *Models Biological


  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. Srivastava, R., Peterson, M.S., and Bentley, W.E.. "Stochastic kinetic analysis of the Escherichia coli stress circuit using sigma(32)-targeted antisense." Biotechnol Bioeng. 75 (1). 2001. pp. 120-9.
    [ PubMed ]

    A stochastic Petri net model was developed for simulating the sigma(32) stress circuit in E. coli. Transcription factor sigma(32) is the principal regulator of the response of E. coli to heat shock. Stochastic Petri net (SPN) models are well suited for kinetics characterization of fluxes in biochemical pathways. Notably, there exists a one-to-one mapping of model tokens and places to molecules of particular species. Our model was validated against experiments in which ethanol (inducer of heat shock response) and sigma(32)-targeted antisense (downward regulator) were used to perturb the sigma(32) regulatory pathway. The model was also extended to simulate the effects of recombinant protein production. Results show that the stress response depends heavily on the partitioning of sigma(32) within the cell; that is, sigma(32) becomes immediately available to mediate a stress response because it exists primarily in a sequestered, inactive form, complexed with chaperones DnaK, DnaJ, and GrpE. Recombinant proteins, however, also compete for chaperone proteins, particularly when folded improperly. Our simulations indicate that when the expression of recombinant protein has a low requirement for DnaK, DnaJ, and GrpE, the overall sigma(32) levels may drop, but the level of heat shock proteins will increase. Conversely, when the overexpressed recombinant protein has a strong requirement for the chaperones, a severe response is predicted. Interestingly, both cases were observed experimentally.

    Keywords: Antisense Elements (Genetics) ; Computer Simulation ; Escherichia coli_*genetics ; Escherichia coli_*metabolism ; Ethanol ; Gene Expression Regulation Bacterial ; Heat-Shock Proteins_genetics ; Heat-Shock Proteins_metabolism ; *Models Biological ; Recombinant Proteins_genetics ; Sigma Factor_*genetics ; Sigma Factor_*metabolism ; Solvents ; Stochastic Processes


  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


  11. Sharov, A.A.. "Self-reproducing systems: structure, niche relations and evolution." Biosystems. 25 (4). 1991. pp. 237-49.
    [ PubMed ]

    A formal definition of a self-reproducing system is proposed using Petri nets. A potential self-reproducing system is a set of places in the Petri net such that the number of tokens in each place increases due to some sequence of internal transitions (a transition is called internal to the marked subset of places if at least one of its starting places and one of its terminating places belongs to that subset). An actual self-reproducing system is a system that compensates the outflow of its components by reproduction. In a suitable environment every potential self-reproducing system becomes an actual one. Each Petri net can be considered as an ecosystem with the web of ecological niches bound together with trophic and other relations. The stationary dynamics of the ecosystem is characterized by the set of filled niches. The process of evolution is described in terms of niche composition change. Perspectives of the theory of self-reproducing systems in biology are discussed.

    Keywords: *Evolution ; Models Biological ; Reproduction ; Selection (Genetics) ; Systems Theory