Bibliography of: Computer Simulation

  1. Goss, P.J. and Peccoud, J.. "Quantitative modeling of stochastic systems in molecular biology by using stochastic Petri nets." Proc Natl Acad Sci U S A. 95 (12). 1998. pp. 6750-5.
    [ .pdf ] [ PubMed ]

    An integrated understanding of molecular and developmental biology must consider the large number of molecular species involved and the low concentrations of many species in vivo. Quantitative stochastic models of molecular interaction networks can be expressed as stochastic Petri nets (SPNs), a mathematical formalism developed in computer science. Existing software can be used to define molecular interaction networks as SPNs and solve such models for the probability distributions of molecular species. This approach allows biologists to focus on the content of models and their interpretation, rather than their implementation. The standardized format of SPNs also facilitates the replication, extension, and transfer of models between researchers. A simple chemical system is presented to demonstrate the link between stochastic models of molecular interactions and SPNs. The approach is illustrated with examples of models of genetic and biochemical phenomena where the ULTRASAN package is used to present results from numerical analysis and the outcome of simulations.

    Keywords: *Computer Simulation ; Human ; *Models Molecular ; *Molecular Biology ; *Stochastic Processes


  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. 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


  6. Matsuno, H., Doi, A., Nagasaki, M., and Miyano, S.. "Hybrid Petri net representation of gene regulatory network." Pac Symp Biocomput. 2000. pp. 341-52.
    [ .pdf ] [ PubMed ]

    It is important to provide a representation method of gene regulatory networks which realizes the intuitions of biologists while keeping the universality in its computational ability. In this paper, we propose a method to exploit hybrid Petri net (HPN) for representing gene regulatory networks. The HPN is an extension of Petri nets which have been used to represent many kinds of systems including stochastic ones in the field of computer sciences and engineerings. Since the HPN has continuous and discrete elements, it can easily handle biological factors such as protein and mRNA concentrations. We demonstrate that, by using HPNs, it is possible to translate biological facts into HPNs in a natural manner. It should be also emphasized that a hierarchical approach is taken for our construction of the genetic switch mechanism of lambda phage which is realized by using HPNs. This hierarchical approach with HPNs makes easier the arrangement of the components in the gene regulatory network based on the biological facts and provides us a prospective view of the network. We also show some computational results of the protein dynamics of the lambda phage mechanism that is simulated and observed by implementing the HPN on a currently available tool.

    Keywords: Bacteriophage lambda_genetics ; Bacteriophage lambda_growth and development ; Computer Simulation ; Gene Expression Regulation ; Gene Expression Regulation Viral ; Genes Viral ; *Models Genetic ; Operon ; Repressor Proteins_genetics ; Stochastic Processes ; Viral Proteins_genetics


  7. 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


  8. Mavrovouniotis, M.L.. "Describing multiple levels of abstraction in the metabolism." Proc Int Conf Intell Syst Mol Biol. vol. 2. 1994. pp. 294-302.
    [ PubMed ]

    We discuss some central issues that arise in the computer representation of the metabolism and its subsystems. We provide a framework for the representation of metabolites and bioreactions at multiple levels of detail. The framework is based on defining an explicit linear mapping of metabolites and reactions from one level of detail to another. A simple reaction mechanism serves as an illustration and shows the emergence of the concept of a catalyst from metabolic abstraction levels.

    Keywords: Catalysis ; *Computer Simulation ; *Metabolism


  9. Reddy, V.N., Liebman, M.N., and Mavrovouniotis, M.L.. "Qualitative analysis of biochemical reaction systems." Comput Biol Med. 26 (1). 1996. pp. 9-24.
    [ PubMed ]

    The qualitative analysis of biochemical reaction systems is presented. A discrete event systems approach is used to represent and analyze bioreaction pathways. The approach is based on Petri nets, which are particularly suited to modeling stoichiometric transformations, i.e. the inter-conversion of metabolites in fixed proportions. The properties and methods for the analysis of Petri nets, along with their interpretation for biochemical systems, are presented. As an example, the combined glycolytic and pentose phosphate pathway of the erythrocyte cell is presented to illustrate the concepts of the methodology.

    Keywords: Biochemistry ; *Computer Simulation ; Erythrocytes_*physiology ; Glycolysis_*physiology ; Human ; Models Theoretical ; Pentosephosphate Pathway_*physiology


  10. 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


  11. 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


  12. 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