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Cell colonies of bacteria, tumour cells and fungi, under nutrient limited growth conditions, exhibit complex branched growth patterns. In order to investigate this phenomenon we present a simple hybrid cellular automaton model of cell…

Biological Physics · Physics 2007-05-23 P. Gerlee , A. R. A Anderson

Growth and shape formation in crowded multicellular assemblies arise from the interplay of chemical gradients, single-cell expansion and mechanical interactions, making it essential to understand how these processes jointly shape collective…

Soft Condensed Matter · Physics 2025-12-02 Ilias-Marios Sarris , Ramin Golestianian , Philip Bittihn

Micropatterned substrates are often used to standardize cell experiments and to quantitatively study the relation between cell shape and function. Moreover, they are increasingly used in combination with traction force microscopy on soft…

Cell Behavior · Quantitative Biology 2015-06-19 Philipp J. Albert , Ulrich S. Schwarz

The applicability of computational and dynamical systems models to organisms is scrutinized, using examples from developmental biology and cognition. Developmental morphogenesis is dependent on the inherent material properties of developing…

Neurons and Cognition · Quantitative Biology 2023-10-24 Stuart A. Newman

The primate heteromodal cortex presents an evident functional modularity at a mesoscopic level, with physiological and anatomical evidence pointing to it as likely substrate of long-term memory. In order to investigate some of its…

Neurons and Cognition · Quantitative Biology 2021-12-09 Carlo Fulvi Mari

In the growth of bacterial colonies, a great variety of complex patterns are observed in experiments, depending on external conditions and the bacterial species. Typically, existing models employ systems of reaction-diffusion equations or…

Biological Physics · Physics 2019-11-12 Lautaro Vassallo , David Hansmann , Lidia A. Braunstein

In this paper we present a simple microscopic stochastic model describing short term plasticity within a large homogeneous network of interacting neurons. Each neuron is represented by its membrane potential and by the residual calcium…

Probability · Mathematics 2020-01-29 Antonio Galves , Eva Löcherbach , Christophe Pouzat , Errico Presutti

In this paper, we consider the problem of learning a predictive model for population cell growth dynamics as a function of the media conditions. We first introduce a generic data-driven framework for training operator-theoretic models to…

Optimization and Control · Mathematics 2020-06-24 Shara Balakrishnan , Aqib Hasnain , Nibodh Boddupalli , Dennis M. Joshy , Robert G. Egbert , Enoch Yeung

In this work, we study a model of the chemostat where the species are present in two forms, isolated bacteria and under an aggregated form like attached bacteria or bacteria in flocks. We show that our general model contains a lot of models…

Dynamical Systems · Mathematics 2012-03-13 Radhoaune Fekih-Salem , Jérôme Harmand , Claude Lobry , Alain Rapaport , Tewfik Sari

In recent years researchers in oil-gas industry have established that the contribution of memory is significant for the modeling of fluid flow in unconventional reservoirs. Mathematically, a memory-based fluid flow model can be described by…

Geophysics · Physics 2018-12-31 Alena Kadyrova , Aleksey Khlyupin

A packed community of exponentially proliferating microbes will spread in size exponentially. However, due to nutrient depletion, mechanical constraints, or other limitations, exponential proliferation is not indefinite, and the spreading…

Biological Physics · Physics 2026-02-02 Meiyi Yao , Joshua M. Jones , Joseph W. Larkin , Andrew Mugler

The regulation of metabolic activity by tuning enzyme expression levels is crucial to sustain cellular growth in changing environments. Metabolic networks are often studied at steady state using constraint-based models and optimization…

Molecular Networks · Quantitative Biology 2014-10-24 Steffen Waldherr , Diego A. Oyarzún , Alexander Bockmayr

Animals behave adaptively in the environment with multiply competing goals. Understanding of the mechanisms underlying such goal-directed behavior remains a challenge for neuroscience as well for adaptive system research. To address this…

Neural and Evolutionary Computing · Computer Science 2012-04-17 Konstantin Lakhman , Mikhail Burtsev

Consider first a memoryless population model described by the usual branching process with a given mean reproduction matrix on a finite space of types. Motivated by the consequences of atavism in Evolutionary Biology, we are interested in a…

Probability · Mathematics 2025-01-03 Jean Bertoin

Motivation: Innovative microfluidic systems carry the promise to greatly facilitate spatio-temporal analysis of single cells under well-defined environmental conditions, allowing novel insights into population heterogeneity and opening new…

Machine Learning · Computer Science 2021-05-18 Dominik Stallmann , Jan P. Göpfert , Julian Schmitz , Alexander Grünberger , Barbara Hammer

Nutrient gradients and limitations play a pivotal role in the life of all microbes, both in their natural habitat as well as in artificial, microfluidic systems. Spatial concentration gradients of nutrients in densely packed cell…

Building mathematical models of brains is difficult because of the sheer complexity of the problem. One potential starting point is through basal cognition, which gives abstract representation of a range of organisms without central nervous…

Neurons and Cognition · Quantitative Biology 2024-11-08 Linnéa Gyllingberg , Yu Tian , David J. T. Sumpter

Synthetic biology aims at designing modular genetic circuits that can be assembled according to the desired function. When embedded in a cell, a circuit module becomes a small subnetwork within a larger environmental network, and its…

Molecular Networks · Quantitative Biology 2019-01-14 Johannes Falk , Leo Bronstein , Maleen Hanst , Barbara Drossel , Heinz Koeppl

World models enable agents to plan within imagined environments by predicting future states conditioned on past observations and actions. However, their ability to plan over long horizons is limited by the effective memory span of the…

Artificial Intelligence · Computer Science 2025-12-09 Eli J. Laird , Corey Clark

Growth mixture models are an important tool for detecting group structure in repeated measures data. Unlike traditional clustering methods, they explicitly model the repeat measurements on observations, and the statistical framework they…

Methodology · Statistics 2017-10-20 Abby Flynt , Nema Dean