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Reaction-diffusion systems have been widely used to study spatio-temporal phenomena in cell biology, such as cell polarization. Coupled bulk-surface models naturally include compartmentalization of cytosolic and membrane-bound polarity…

Pattern Formation and Solitons · Physics 2020-08-11 Frédéric Paquin-Lefebvre , Bin Xu , Kelsey L. DiPietro , Alan E. Lindsay , Alexandra Jilkine

Three coarse-grained molecular dynamics (MD) models are investigated with the aim of developing and analyzing multiscale methods which use MD simulations in parts of the computational domain and (less detailed) Brownian dynamics (BD)…

Computational Physics · Physics 2015-06-18 Radek Erban

Pattern formation often occurs in confined systems, yet how boundaries shape patterning dynamics is unclear. We develop techniques to analyze confinement effects in nonlocal advection-diffusion equations, which generically capture the…

Pattern Formation and Solitons · Physics 2025-09-11 Jan Rombouts , Michael L Zhao , Alexander Aulehla , Anna Erzberger

Protein structure prediction and folding are fundamental to understanding biology, with recent deep learning advances reshaping the field. Diffusion-based generative models have revolutionized protein design, enabling the creation of novel…

Machine Learning · Computer Science 2025-10-01 Yogesh Verma , Markus Heinonen , Vikas Garg

Reaction-diffusion models with nonlocal constraints naturally arise as limiting cases of coupled bulk-surface models of intracellular signalling. In this paper, a minimal, mass-conserving model of cell-polarization on a curved membrane is…

Pattern Formation and Solitons · Physics 2022-10-04 Pearson W. Miller , Daniel Fortunato , Matteo Novaga , Stanislav Y. Shvartsman , Cyrill B. Muratov

We introduce a general theoretical framework to study the shape dynamics of actively growing and remodeling surfaces. Using this framework we develop a physical model for growing bacterial cell walls and study the interplay of cell shape…

Biological Physics · Physics 2016-04-08 Shiladitya Banerjee , Norbert F. Scherer , Aaron R. Dinner

Developments in dynamical systems theory provides new support for the macroscale modelling of pdes and other microscale systems such as Lattice Boltzmann, Monte Carlo or Molecular Dynamics simulators. By systematically resolving subgrid…

Numerical Analysis · Mathematics 2012-01-18 A. J. Roberts , Tony MacKenzie , J. E. Bunder

Real-world applications of computational fluid dynamics often involve the evaluation of quantities of interest for several distinct geometries that define the computational domain or are embedded inside it. For example, design optimization…

Numerical Analysis · Mathematics 2023-08-08 Guglielmo Padula , Francesco Romor , Giovanni Stabile , Gianluigi Rozza

Recent advances in high-resolution experimental methods have highlighted the significance of cell signal pathway crosstalk and localised signalling activity in the development and disease of numerous biological systems. The investigation of…

Dynamical Systems · Mathematics 2022-09-19 Joshua W. Moore , Trevor C. Dale , Thomas E. Woolley

Diffusion models are important in tissue engineering as they enable an understanding of molecular delivery to cells in tissue constructs. As three-dimensional (3D) tissue constructs become larger, more intricate, and more clinically…

Tissues and Organs · Quantitative Biology 2015-12-22 Richard J. McMurtrey

Cells contain elaborate and interconnected networks of protein polymers which make up the cytoskeleton. The cytoskeleton governs the internal positioning and movement of vesicles and organelles, and controls dynamic changes in cell…

Biological Physics · Physics 2017-01-24 Lishibanya Mohapatra , Bruce L. Goode , Predrag Jelenkovic , Rob Phillips , Jane Kondev

Recent advancements in the ability to construct three-dimensional (3D) tissues and organoids from stem cells and biomaterials have not only opened abundant new research avenues in disease modeling and regenerative medicine but also have…

Tissues and Organs · Quantitative Biology 2017-07-27 Richard J. McMurtrey

Interactions between neighboring cells are essential for generating or refining patterns in a number of biological systems. We propose a discrete filtering approach to predict how networks of cells modulate spatially varying input signals…

Tissues and Organs · Quantitative Biology 2019-02-14 Melinda Liu Perkins , Murat Arcak

In densely-packed two-dimensional systems of growing cells, such as rod-shaped bacteria, a number of experimental and numerical studies report distinct patterns of nematic orientational order in the presence of confinement. So far, these…

Soft Condensed Matter · Physics 2025-06-13 Lukas Hupe , Jonas Isensee , Ramin Golestanian , Philip Bittihn

The Dynamic Template model of biological cell membranes and the cytoplasm as spatially organised fluid layers is extended to plant cells, and is shown to offer a feasible shear driven mechanism for the co-alignment of internal and external…

General Physics · Physics 2008-07-15 J. T. Lofthouse

Dimensionality reduction represents a crucial step in extracting meaningful insights from Molecular Dynamics (MD) simulations. Conventional approaches, including linear methods such as principal component analysis as well as various…

Soft Condensed Matter · Physics 2025-10-10 Georg Diez , Nele Dethloff , Gerhard Stock

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

Proteins control many vital functions in living cells, such as cell growth and cell division. Reliable coordination of these functions requires the spatial and temporal organizaton of proteins inside cells, which encodes information about…

Biological Physics · Physics 2022-02-22 Tom Burkart , Manon C. Wigbers , Laeschkir Würthner , Erwin Frey

Protein structure prediction is pivotal for understanding the structure-function relationship of proteins, advancing biological research, and facilitating pharmaceutical development and experimental design. While deep learning methods and…

Machine Learning · Computer Science 2024-12-30 Kaihui Cheng , Ce Liu , Qingkun Su , Jun Wang , Liwei Zhang , Yining Tang , Yao Yao , Siyu Zhu , Yuan Qi

Phase separation within polymer networks plays a central role in shaping the structure and mechanics of both synthetic materials and living cells, including the formation of biomolecular condensates within cytoskeletal networks. Previous…

Soft Condensed Matter · Physics 2025-12-01 Takahiro Yokoyama , Yicheng Qiang , David Zwicker , Arash Nikoubashman