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Related papers: Michaelis-Menten dynamics in protein subnetworks

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Computer algebra methods for analyzing reaction networks often rely on the assumption of mass-action kinetics, which transform the governing ODEs into polynomial systems amenable to techniques such as Gr\"obner basis computation and related…

Molecular Networks · Quantitative Biology 2025-11-19 Richard Golnik , Thomas Gatter , Peter F. Stadler , Nicola Vassena

Motor proteins are active enzymatic molecules that drive a variety of biological processes, including transfer of genetic information, cellular transport, cell motility and muscles contraction. It is known that these biological molecular…

Soft Condensed Matter · Physics 2018-01-17 Luiza V. F. Gomes , Anatoly B. Kolomeisky

The abundance of data affords researchers to pursue more powerful computational tools to learn the dynamics of complex system, such as neural networks, engineered systems and social networks. Traditional machine learning approaches capture…

Machine Learning · Computer Science 2024-05-16 Yan Shen , Fan Yang , Mingchen Gao , Wen Dong

The chapter presents some new approaches to describing the collective behavior of complex systems of mathematical biology based on the evolution equations of observables such as open systems. This representation of kinetic evolution has…

Mathematical Physics · Physics 2025-03-18 V. I. Gerasimenko

Recent work of M.D. Johnston et al. has produced sufficient conditions on the structure of a chemical reaction network which guarantee that the corresponding discrete state space system exhibits an extinction event. The conditions consist…

Optimization and Control · Mathematics 2017-01-11 Matthew D. Johnston

An algorithm is given in this paper for the computation of dynamically equivalent weakly reversible realizations with the maximal number of reactions, for chemical reaction networks (CRNs) with mass action kinetics. The original problem…

Dynamical Systems · Mathematics 2011-07-05 Gabor Szederkenyi , Katalin M. Hangos , Zsolt Tuza

Predicting enzyme kinetic parameters quantifies how efficiently an enzyme catalyzes a specific substrate under defined biochemical conditions. Canonical parameters such as the turnover number ($k_\text{cat}$), Michaelis constant…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Fei Wang , Xinye Zheng , Kun Li , Yanyan Wei , Yuxin Liu , Ganpeng Hu , Tong Bao , Jingwen Yang

In most natural sciences there is currently the insight that it is necessary to bridge gaps between different processes which can be observed on different scales. This is especially true in the field of chemical reactions where the…

Molecular Networks · Quantitative Biology 2008-03-03 L. Sbano , M. Kirkilionis

In biochemical systems the Michaelis-Menten (MM) scheme is one of the best-known models of the enzyme- catalyzed kinetics. In the academic literature the MM approximation has been thoroughly studied in the context of differential equation…

Chemical Physics · Physics 2015-01-13 Vahe Galstyan

In the study of dynamics on networks, moment closure is a commonly used method to obtain low-dimensional evolution equations amenable to analysis. The variables in the evolution equations are mean counts of subgraph states and are referred…

Dynamical Systems · Mathematics 2022-12-07 Bert Wuyts , Jan Sieber

Chemical reaction networks describe interactions between biochemical species. Once an underlying reaction network is given for a biochemical system, the system dynamics can be modelled with various mathematical frameworks such as continuous…

Probability · Mathematics 2023-06-22 German Enciso , Radek Erban , Jinsu Kim

We present a systematic mathematical analysis of the qualitative steady-state response to rate perturbations in large classes of reaction networks. This includes multimolecular reactions and allows for catalysis, enzymatic reactions,…

Dynamical Systems · Mathematics 2017-11-22 Bernhard Brehm , Bernold Fiedler

Over the last two decades, network science has greatly advanced our understanding of how the collective behaviors of a complex system emerge from the interactions among its basic units. Multiplex networks, i.e. networks with many layers,…

Mathematical modeling has broad applications in neuroscience whether modeling the dynamics of a single synapse or an entire network of neurons. In Part I, we model vesicle replenishment and release at the photoreceptor synapse to better…

Neurons and Cognition · Quantitative Biology 2017-02-23 Caitlyn M. Parmelee

This paper is an introduction to the membrane potential equation for neurons. Its properties are described, as well as sample applications. Networks of these equations can be used for modeling neuronal systems, which also process images and…

Neurons and Cognition · Quantitative Biology 2018-01-29 Matthias S. Keil

Network inference approaches are now widely used in biological applications to probe regulatory relationships between molecular components such as genes or proteins. Many methods have been proposed for this setting, but the connections and…

Applications · Statistics 2014-06-03 Chris. J. Oates , Sach Mukherjee

Encoding models are used for predicting brain activity in response to sensory stimuli with the objective of elucidating how sensory information is represented in the brain. Encoding models typically comprise a nonlinear transformation of…

Neurons and Cognition · Quantitative Biology 2017-03-13 Umut Güçlü , Marcel A. J. van Gerven

The high computational cost of evaluating atomic interactions recently motivated the development of computationally inexpensive kinetic models, which can be parametrized from MD simulations of complex chemistry of thousands of species or…

Computational Physics · Physics 2021-05-14 Vincent Dufour-Décieux , Rodrigo Freitas , Evan J. Reed

Synthesis of protein molecules in a cell are carried out by ribosomes. A ribosome can be regarded as a molecular motor which utilizes the input chemical energy to move on a messenger RNA (mRNA) track that also serves as a template for the…

Biological Physics · Physics 2009-07-12 Ashok Garai , Debanjan Chowdhury , Debashish Chowdhury , T. V. Ramakrishnan

Reaction mechanism search tools have demonstrated the ability to provide insights into likely products and rate-limiting steps of reacting systems. However, reactions involving several concerted bond changes - as can be found in many key…

Machine Learning · Computer Science 2025-10-15 Nicholas Casetti , Dylan Anstine , Olexandr Isayev , Connor W. Coley