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<title lang=en>Twelve competing ways to recover the Michaelis-Menten equation reveal the alternative approaches to steady state modeling</title>
<creator>Michel, Denis</creator>
<creator>Ruelle, Philippe</creator>
<contributor>TREC : Transcription, Environment and Cancer ; Institut de recherche, santé, environnement et travail [Rennes] (Irset) ; Université d'Angers (UA) - Université des Antilles et de la Guyane (UAG) - Université de Rennes 1 (UR1) - École des Hautes Études en Santé Publique [EHESP] (EHESP) - Institut National de la Santé et de la Recherche Médicale (INSERM) - Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ) - Université d'Angers (UA) - Université des Antilles et de la Guyane (UAG) - Université de Rennes 1 (UR1) - École des Hautes Études en Santé Publique [EHESP] (EHESP) - Institut National de la Santé et de la Recherche Médicale (INSERM) - Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )</contributor>
<contributor>Institut de Recherche en Mathématiques et Physique (UCL IRMP) ; Université Catholique de Louvain (UCL)</contributor>
<description>International audience</description>
<source>ISSN: 0259-9791</source>
<source>EISSN: 1572-8897</source>
<source>Journal of Mathematical Chemistry</source>
<publisher>Springer Verlag (Germany)</publisher>
<identifier>hal-00920806</identifier>
<identifier>https://hal-univ-rennes1.archives-ouvertes.fr/hal-00920806</identifier>
<identifier>https://hal-univ-rennes1.archives-ouvertes.fr/hal-00920806v2/document</identifier>
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<source>https://hal-univ-rennes1.archives-ouvertes.fr/hal-00920806</source>
<source>Journal of Mathematical Chemistry, Springer Verlag (Germany), 2013, 51 (9), pp.2271-2284. 〈10.1007/s10910-013-0237-5〉</source>
<identifier>ARXIV : 1312.5468</identifier>
<relation>info:eu-repo/semantics/altIdentifier/arxiv/1312.5468</relation>
<identifier>DOI : 10.1007/s10910-013-0237-5</identifier>
<relation>info:eu-repo/semantics/altIdentifier/doi/10.1007/s10910-013-0237-5</relation>
<language>en</language>
<subject lang=en>Random walk</subject>
<subject lang=en>Steady-state</subject>
<subject lang=en>Stochastic reaction chain</subject>
<subject lang=en>Enzyme kinetics</subject>
<subject>[PHYS.PHYS.PHYS-CHEM-PH] Physics [physics]/Physics [physics]/Chemical Physics [physics.chem-ph]</subject>
<subject>[CHIM.THEO] Chemical Sciences/Theoretical and/or physical chemistry</subject>
<type>info:eu-repo/semantics/article</type>
<type>Journal articles</type>
<description lang=en>The Michaelis-Menten enzymatic reaction is sufficient to perceive many subtleties of network modeling, including the concentration and time scales separations, the formal equivalence between bulk phase and single-molecule approaches, or the relationships between single-cycle transient probabilities and steady state rates. Twelve methods proposed by different authors and yielding the same famous Michaelis-Menten equation, are selected here to illustrate the kinetic and probabilistic use of rate constants and to review basic techniques for handling them. Finally, the general rate of an ordered multistep reaction, of which the Michaelis-Menten reaction is a particular case, is deduced from a Markovian approach.</description>
<date>2013-10</date>
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