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Reaction Networks, Oscillatory Motifs and Parameter Estimation in Biochemical Systems

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F19%3A00509644" target="_blank" >RIV/86652079:_____/19:00509644 - isvavai.cz</a>

  • Výsledek na webu

    <a href="http://dx.doi.org/10.1007/978-3-030-28042-0_3" target="_blank" >http://dx.doi.org/10.1007/978-3-030-28042-0_3</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-28042-0_3" target="_blank" >10.1007/978-3-030-28042-0_3</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Reaction Networks, Oscillatory Motifs and Parameter Estimation in Biochemical Systems

  • Popis výsledku v původním jazyce

    We outline an approach to analysis of dynamics of biosystems formulated as reaction networks. In particular, we discuss stability analysis provided that stoichiometric equations are given for each reaction step together with power law rate expressions. Based on stoichiometry alone, the network at stationary state can be decomposed into elementary subnetworks (elementary modes, extreme currents, fluxes). Assuming power law kinetics, the capacity of the elementary subnetworks for displaying dynamical instabilities, such as bistability and oscillations, is evaluated. These subnetworks are then suitably combined to form the entire network satisfying certain stability constraints implied by experiments. Specifically, we assume that an experimentally measured biosystem represented by a reaction network displays an experimentally observed change from a steady state to oscillations. For the assumed reaction mechanism only a limited set kinetic parameters is known. In contrast, input/output parameters are known from the experiment. The set of unknown kinetic parameters may be estimated by finding a suitable linear combination of elementary modes via linear optimization so that the dynamics displayed by the model fits the experimentally observed behavior. Moreover, reaction network theory is useful in identifying subnetworks that are destabilizing the steady state to yield oscillations. Such subnetworks are called oscillatory motifs and possess a characteristic topology. As an example, we analyze a carbon-nitrogen metabolism of cyanobacteria and examine its oscillatory dynamics.nKlíčová slova: reaction networks, oscillatory dynamics, kinetic parameter estimation

  • Název v anglickém jazyce

    Reaction Networks, Oscillatory Motifs and Parameter Estimation in Biochemical Systems

  • Popis výsledku anglicky

    We outline an approach to analysis of dynamics of biosystems formulated as reaction networks. In particular, we discuss stability analysis provided that stoichiometric equations are given for each reaction step together with power law rate expressions. Based on stoichiometry alone, the network at stationary state can be decomposed into elementary subnetworks (elementary modes, extreme currents, fluxes). Assuming power law kinetics, the capacity of the elementary subnetworks for displaying dynamical instabilities, such as bistability and oscillations, is evaluated. These subnetworks are then suitably combined to form the entire network satisfying certain stability constraints implied by experiments. Specifically, we assume that an experimentally measured biosystem represented by a reaction network displays an experimentally observed change from a steady state to oscillations. For the assumed reaction mechanism only a limited set kinetic parameters is known. In contrast, input/output parameters are known from the experiment. The set of unknown kinetic parameters may be estimated by finding a suitable linear combination of elementary modes via linear optimization so that the dynamics displayed by the model fits the experimentally observed behavior. Moreover, reaction network theory is useful in identifying subnetworks that are destabilizing the steady state to yield oscillations. Such subnetworks are called oscillatory motifs and possess a characteristic topology. As an example, we analyze a carbon-nitrogen metabolism of cyanobacteria and examine its oscillatory dynamics.nKlíčová slova: reaction networks, oscillatory dynamics, kinetic parameter estimation

Klasifikace

  • Druh

    C - Kapitola v odborné knize

  • CEP obor

  • OECD FORD obor

    10608 - Biochemistry and molecular biology

Návaznosti výsledku

  • Projekt

    <a href="/cs/project/GA18-24397S" target="_blank" >GA18-24397S: Analýza reakčních sítí s omezujícími podmínkami - nástroj pro experimentální validaci modelů biochemických a fotobiologických reaktorů</a><br>

  • Návaznosti

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Ostatní

  • Rok uplatnění

    2019

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název knihy nebo sborníku

    Lecture Notes in Computer Science

  • ISBN

    978-3-030-28041-3

  • Počet stran výsledku

    11

  • Strana od-do

    30-41

  • Počet stran knihy

    199

  • Název nakladatele

    Springer Nature Switzerland AG

  • Místo vydání

    Switzerland

  • Kód UT WoS kapitoly

    000509932800003