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Gene expression time delays, modelling the complex biological processes of gene transcription and translation, have been shown to play an important role in cellular dynamics. Time delays, motivated by the gene expression process, can also…

Cell Behavior · Quantitative Biology 2022-02-24 Alec Sargood

In systems of active programmable matter, individual modules require a constant supply of energy to participate in the system's collective behavior. These systems are often powered by an external energy source accessible by at least one…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-07-21 Joshua J. Daymude , Andréa W. Richa , Jamison W. Weber

Background: Mechanotransduction in bone cells plays a pivotal role in osteoblast differentiation and bone remodelling. Mechanotransduction provides the link between modulation of the extracellular matrix and intracellular actions. By…

Subcellular Processes · Quantitative Biology 2019-02-26 Gianluca Ascolani , Timothy M. Skerry , Damien Lacroix , Enrico Dall'Ara , Aban Shuaib

Working towards the development of an evolvable cancer treatment simulator, the investigation of Differential Evolution was considered, motivated by the high efficiency of variations of this technique in real-valued problems. A basic DE…

Neural and Evolutionary Computing · Computer Science 2020-03-27 Michail-Antisthenis Tsompanas , Larry Bull , Andrew Adamatzky , Igor Balaz

We propose and study a strongly coupled PDE-ODE-ODE system modeling cancer cell invasion through a tissue network under the go-or-grow hypothesis asserting that cancer cells can either move or proliferate. Hence our setting features two…

Analysis of PDEs · Mathematics 2016-05-31 Anna Zhigun , Christina Surulescu , Alexander Hunt

Life is commonly described as a self-organized, far-from-equilibrium process that maintains internal order by consuming free energy and exporting entropy. This thermodynamic view underlies diverse theoretical frameworks -- from autopoiesis…

Biological Physics · Physics 2025-12-23 Didier Sornette , Virgile Troude

Chemical kinetics mechanisms are essential for understanding, analyzing, and simulating complex combustion phenomena. In this study, a Neural Ordinary Differential Equation (Neural ODE) framework is employed to optimize kinetics parameters…

Chemical Physics · Physics 2022-09-07 Xingyu Su , Weiqi Ji , Jian An , Zhuyin Ren , Sili Deng , Chung K. Law

Business Process Simulation (BPS) is a critical tool for analyzing and improving organizational processes by estimating the impact of process changes. A key component of BPS is the case-arrival model, which determines the pattern of new…

Machine Learning · Computer Science 2025-05-29 Lukas Kirchdorfer , Konrad Özdemir , Stjepan Kusenic , Han van der Aa , Heiner Stuckenschmidt

A large variety of real systems are composed by entities in relationships which can be represented by networks. In many of these systems, elements are embedded in the space and location information impacts properties and evolution. Local…

Physics and Society · Physics 2021-11-09 Michele Tirico , Stefan Balev , Antoine Dutot , Damien Olivier

The dynamics of flow within a material transport network is dependent upon the dynamics of its power source. Responding to a change of these dynamics is critical for the fitness of living flow networks, e.g. the animal vasculature, which…

Fluid Dynamics · Physics 2021-09-29 Sean Fancher , Eleni Katifori

Large multidimensionality of high-throughput datasets pertaining to cell signaling and gene regulation renders it difficult to extract mechanisms underlying the complex kinetics involving various biochemical compounds (e.g., proteins,…

Quantitative Methods · Quantitative Biology 2012-01-25 Michael Dworkin , Sayak Mukherjee , Ciriyam Jayaprakash , Jayajit Das

Chemical kinetics plays an important role in governing the thermal evolution in reactive flows problems. The possible interactions between chemical species increase drastically with the number of species considered in the system. Various…

Instrumentation and Methods for Astrophysics · Physics 2022-07-18 Kwok Sun Tang , Matthew Turk

First, we briefly describe the general growth mechanism, which governs the growth of living organisms, and its mathematical representation, the growth equation. Using the growth equation, we compute growth curve for S. cerevisiae and show…

Other Quantitative Biology · Quantitative Biology 2013-02-19 Yuri K. Shestopaloff

Mathematical modelling of the evolution of the size-spectrum dynamics in aquatic ecosystems was discovered to be a powerful tool to have a deeper insight into impacts of human- and environmental driven changes on the marine ecosystem. In…

Analysis of PDEs · Mathematics 2024-01-02 Laura Kanzler , Benoit Perthame , Benoit Sarels

Reaction-diffusion equations describe various spatially extended processes that unfold as traveling fronts moving at constant velocity. We introduce and solve analytically a model that, besides such fronts, supports solutions advancing as…

Biological Physics · Physics 2026-02-13 Louis Brezin , Kyle J. Shaffer , Kirill S. Korolev

A chemical reaction network (CRN) is composed of reactions that can be seen as interactions among entities called species, which exist within the system. Endowed with kinetics, CRN has a corresponding set of ordinary differential equations…

Dynamical Systems · Mathematics 2021-04-20 Bryan S. Hernandez , Ralph John L. De la Cruz

The nature of dark energy (DE) remains elusive, even though it constitutes the dominant energy-density component of the Universe and drives the late-time acceleration of cosmic expansion. By combining measurements of the expansion history…

Proteins are macromolecules that mediate a significant fraction of the cellular processes that underlie life. An important task in bioengineering is designing proteins with specific 3D structures and chemical properties which enable…

Quantitative Methods · Quantitative Biology 2022-05-31 Namrata Anand , Tudor Achim

Network models are widely used as structural summaries of biochemical systems. Statistical estimation of networks is usually based on linear or discrete models. However, the dynamics of these systems are generally nonlinear, suggesting that…

Applications · Statistics 2014-06-03 C. J. Oates , F. Dondelinger , N. Bayani , J. Korola , J. W. Gray , S. Mukherjee

We show that neural networks trained by evolutionary reinforcement learning can enact efficient molecular self-assembly protocols. Presented with molecular simulation trajectories, networks learn to change temperature and chemical potential…

Statistical Mechanics · Physics 2020-06-01 Stephen Whitelam , Isaac Tamblyn
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