Toward a systematic determination of complex reaction mechanisms

Chevalier, Tim; Schreiber, Igor; Ross, John D.

doi:10.1021/j100128a006

Cited by 70 publications

(84 citation statements)

References 9 publications

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“…16,17 In physics and chemistry, oscillations have been observed in many complex reaction mixtures. 18 The study of various features of oscillations appeared to be useful for determining the essential parts of complex reaction mechanisms. [18][19][20] In biology, limit cycle systems are of particular interest, since some of them provide the mechanisms for various biological clocks, including the one governing the cell cycle.…”

Section: Introductionmentioning

confidence: 99%

“…18 The study of various features of oscillations appeared to be useful for determining the essential parts of complex reaction mechanisms. [18][19][20] In biology, limit cycle systems are of particular interest, since some of them provide the mechanisms for various biological clocks, including the one governing the cell cycle. 21,22 Metabolic oscillations occur in yeast extracts, in populations of yeast cells (see, for example, refs [23][24][25][26][27][28][29][30][31][32], and in photosynthesis.…”

Section: Introductionmentioning

confidence: 99%

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Control Analysis of Periodic Phenomena in Biological Systems

1997

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Control analysis of periodic phenomena in biological systemsKholodenko, B.N.; Demin, O.V.; Westerhoff, H.V. General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. Download date: 10 May 2018 Control Analysis of Periodic Phenomena in Biological SystemsBoris N. Kholodenko,* , † Oleg V. Demin, ‡ and Hans V. Westerhoff §,| Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson UniVersity, 1020 Locust Street, Philadelphia, PennsylVania 19107, A.N. Belozersky Institute of Physico-Chemical Biology, Moscow State UniVersity, 119899 Moscow, Russia, Department of Microbial Physiology, Free UniVersity, De Boelelaan 1087, NL-1081 HV Amsterdam, The Netherlands, and E. C. Slater Institute, Biocentrum, UniVersity of Amsterdam, Plantage Muidergracht 12, The Netherlands ReceiVed: July 31, 1996 In Final Form: January 7, 1997 X Principles of the control and regulation of steady-state metabolic systems have been identified in terms of the concepts and laws of metabolic control analysis (MCA). With respect to the control of periodic phenomena MCA has not been equally successful. This paper shows why in case of autonomous (self-sustained) oscillations for the concentrations and reaction rates, time-dependent control coefficients are not useful to characterize the system: they are neither constant nor periodic and diverge as time progresses. This is because a controlling parameter tends to change the frequency and causes a phase shift that continuously increases with time. This recognition is important in the extension of MCA for periodic phenomena. For oscillations that are enforced with an externally determined frequency, the time-dependent control coefficients over metabolite concentration and fluxes (reaction rates) are shown to have a complete meaning. Two such time-dependent control coefficients are defined for forced oscillations. One, the so-called periodic control coefficient, measures how the stationary periodic movement depends on the activities of one of the enzymes. The other, the socalled transient control coefficient, measures the control over the transition of the system between two stationary oscillations, as induced by a change in one of the enzyme activities. For forced oscillations, the two control coefficients become equal as time tends to infinity. N...

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Control Analysis of Periodic Phenomena in Biological Systems

1997

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“…A recent review of available techniques can be found in [2] or [3], but earlier articles, such as [4], also list several approaches to this network identification problem.…”

Section: Related Workmentioning

confidence: 99%

Determining Interconnections in Chemical Reaction Networks

Papachristodoulou

Recht

2007

2007 American Control Conference

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Abstract-We present a methodology for robust determination of chemical reaction network interconnections. Given time series data that are collected from experiments and taking into account the measurement error, we minimize the 1-norm of the decision variables (reaction rates) keeping the data in close Euler-fit with a general model structure based on mass action kinetics which models the species' dynamics. We illustrate our methodology on a hypothetical chemical reaction network under various experimental scenarios.

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“…The objective, is to provide guidelines to the user to determine the size of reaction network from the available data. The usual approach dedicated to the determination of reaction networks relies on the linearisation of the dynamics around a reference solution (Eiswirth et al, 1991;Chevalier et al, 1993) and identification of the local Jacobian matrix. Here, in the spirit of (Chen and Bastin, 1996;Bernard and Bastin, 2005), we exploit the structure of the bioprocess (equation (1)) and our arguments do not rely on any linearisation.…”

Section: Introductionmentioning

confidence: 99%

Can we assess the model complexity for a bioprocess: theory and example of the anaerobic digestion process

Bernard

Chachuat

Hélias

et al. 2006

Water Science and Technology

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In this paper we propose a methodology to determine the structure of the pseudo-stoichiometric coefficient matrix K in a mass balance based model, i.e. the maximal number of biomasses that must be taken into account to reproduce an available data set. It consists in estimating the number of reactions that must be taken into account to represent the main mass transfer within the bioreactor. This provides the dimension of K. The method is applied to data from an anaerobic digestion process and shows that even a model including a single biomass is sufficient. Then we apply the same method to the "synthetic data" issued from the complex ADM1 model, showing that the main model features can be obtained with 2 biomasses.

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Toward a systematic determination of complex reaction mechanisms

Cited by 70 publications

References 9 publications

Control Analysis of Periodic Phenomena in Biological Systems

Control Analysis of Periodic Phenomena in Biological Systems

Determining Interconnections in Chemical Reaction Networks

Can we assess the model complexity for a bioprocess: theory and example of the anaerobic digestion process

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