Bibliography of: Models Chemical

  1. Hofestadt, R. and Meineke, F.. "Interactive modelling and simulation of biochemical networks." Comput Biol Med. 25 (3). 1995. pp. 321-34.
    [ PubMed ]

    The analysis of biochemical processes can be supported using methods of modelling and simulation. New methods of computer science are discussed in this field of research. This paper presents a new method which allows the modelling and analysis of complex metabolic networks. Moreover, our simulation shell is based on this formalization and represents the first tool for the interactive simulation of metabolic processes.

    Keywords: *Biochemistry ; Cell Communication_physiology ; Databases Factual ; Enzymes_physiology ; Gene Expression_physiology ; Genes Regulator_physiology ; Genetic Diseases Inborn_enzymology ; Genetic Diseases Inborn_genetics ; Genetic Diseases Inborn_metabolism ; *Metabolism ; *Models Chemical ; *Models Genetic ; Probability ; *Software


  2. 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


  3. Zauner, K.P. and Conrad, M.. "Enzymatic computing." Biotechnol Prog. 17 (3). 2001. pp. 553-9.
    [ .pdf ] [ PubMed ]

    The conformational dynamics of enzymes is a computational resource that fuses milieu signals in a nonlinear fashion. Response surface methodology can be used to elicit computational functionality from enzyme dynamics. We constructed a tabletop prototype to implement enzymatic signal processing in a device context and employed it in conjunction with malate dehydrogenase to perform the linearly inseparable exclusive-or operation. This shows that proteins can execute signal processing operations that are more complex than those performed by individual threshold elements. We view the experiments reported, though restricted to the two-variable case, as a stepping stone to computational networks that utilize the precise reproducibility of proteins, and the concomitant reproducibility of their nonlinear dynamics, to implement complex pattern transformations.

    Keywords: Calcium_chemistry ; Calcium_metabolism ; Enzymes_*chemistry ; Enzymes_*metabolism ; Image Processing ; Computer-Assisted ; Magnesium_chemistry ; Magnesium_metabolism ; Malate Dehydrogenase_chemistry ; Malate Dehydrogenase_metabolism ; Models Chemical ; *Models Molecular ; Osmolar Concentration ; Protein Conformation