Using Structural Kinetic Modeling To Identify Key Determinants of Stability in Reaction Networks

Carbonaro, Nicole J.; Thorpe, Ian F.

doi:10.1021/acs.jpca.7b01852

Cited by 5 publications

(3 citation statements)

References 38 publications

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“…Expanding on the relations between COT and not only these reaction networks frameworks, but also other interesting frameworks, such as structural kinetic modeling [36] and pathway analysis [37], and others [38], allows for a deeper description of the notion of goal and suggest the existence of different classes of goals, each of them operationalized differently as shown in Table 1.…”

Section: Discussionmentioning

confidence: 99%

Goal Directedness, Chemical Organizations, and Cybernetic Mechanisms

Busseniers

Veloz

Heylighen

2021

Entropy

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In this article, we attempt at developing a scenario for the self-organization of goal-directed systems out of networks of (chemical) reactions. Related scenarios have been proposed to explain the origin of life starting from autocatalytic sets, but these sets tend to be too unstable and dependent on their environment to maintain. We apply instead a framework called Chemical Organization Theory (COT), which shows mathematically under which conditions reaction networks are able to form self-maintaining, autopoietic organizations. We introduce the concepts of perturbation, action, and goal based on an operationalization of the notion of change developed within COT. Next, we incorporate the latter with notions native to the theory of cybernetics aimed to explain goal directedness: reference levels and negative feedback among others. To test and refine these theoretical results, we present some examples that illustrate our approach. We finally discuss how this could result in a realistic, step-by-step scenario for the evolution of goal directedness, thus providing a theoretical solution to the age-old question of the origins of purpose.

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Section: Discussionmentioning

confidence: 99%

Goal Directedness, Chemical Organizations, and Cybernetic Mechanisms

Busseniers

Veloz

Heylighen

2021

Entropy

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“…These and other findings were later confirmed in Gehrmann et al (2011), who used GM to analyze a more complex model of glycolysis. Carbonaro and Thorpe (2017) applied structural kinetic modeling to determine metabolic components that are major contributors to network stability in complex metabolic networks associated with glycolysis and pentose phosphate pathway and to predict the impact of perturbations on these components.…”

Section: Models Of Metabolismmentioning

confidence: 99%

Generalized Structural Kinetic Modeling: A Survey and Guide

Massing

Groß

2022

Front. Mol. Biosci.

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Many current challenges involve understanding the complex dynamical interplay between the constituents of systems. Typically, the number of such constituents is high, but only limited data sources on them are available. Conventional dynamical models of complex systems are rarely mathematically tractable and their numerical exploration suffers both from computational and data limitations. Here we review generalized modeling, an alternative approach for formulating dynamical models to gain insights into dynamics and bifurcations of uncertain systems. We argue that this approach deals elegantly with the uncertainties that exist in real world data and enables analytical insight or highly efficient numerical investigation. We provide a survey of recent successes of generalized modeling and a guide to the application of this modeling approach in future studies such as complex integrative ecological models.

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“…This method has been used in different ways. For instance, in [19,20], it is used to analyse the stability of metabolic equilibria. In [21], Girbig et al combine it with supervised machine learning to detect patterns of enzyme-metabolite interactions that have a major role in the stability of the system.…”

Section: Using Kinetic Models To Analyse the Dynamics Of Metabolismmentioning

confidence: 99%

Combining Kinetic and Constraint-Based Modelling to Better Understand Metabolism Dynamics

2021

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To understand the phenotypic capabilities of organisms, it is useful to characterise cellular metabolism through the analysis of its pathways. Dynamic mathematical modelling of metabolic networks is of high interest as it provides the time evolution of the metabolic components. However, it also has limitations, such as the necessary mechanistic details and kinetic parameters are not always available. On the other hand, large metabolic networks exhibit a complex topological structure which can be studied rather efficiently in their stationary regime by constraint-based methods. These methods produce useful predictions on pathway operations. In this review, we present both modelling techniques and we show how they bring complementary views of metabolism. In particular, we show on a simple example how both approaches can be used in conjunction to shed some light on the dynamics of metabolic networks.

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Using Structural Kinetic Modeling To Identify Key Determinants of Stability in Reaction Networks

Cited by 5 publications

References 38 publications

Goal Directedness, Chemical Organizations, and Cybernetic Mechanisms

Goal Directedness, Chemical Organizations, and Cybernetic Mechanisms

Generalized Structural Kinetic Modeling: A Survey and Guide

Combining Kinetic and Constraint-Based Modelling to Better Understand Metabolism Dynamics

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