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We propose a three dimensional mechanical model of embryonic tissue dynamics. Mechanically coupled adherent cells are represented as particles interconnected with elastic beams which can exert non-central forces and torques. Tissue…

生物物理 · 物理学 2015-06-22 Andras Czirok , Dona Greta Isai

Mineralized collagen microfibrils in human bone provide its mechanical properties (stiffness, elasticity, ductility, energy dissipation and strength). However, detailed 3D finite element models describing the mechanical behaviour of the…

组织与器官 · 定量生物学 2012-03-01 Ridha Hambli , Abdelwahed Barkaoui

During their evolution, proteins explore sequence space via an interplay between random mutations and phenotypic selection. Here we build upon recent progress in reconstructing data-driven fitness landscapes for families of homologous…

生物大分子 · 定量生物学 2022-01-28 Matteo Bisardi , Juan Rodriguez-Rivas , Francesco Zamponi , Martin Weigt

A multiphasic constitutive model of the skin that implicitly accounts for the process of intrinsic (i.e.\ chronological) ageing via variation of the constitutive parameters is proposed. The structurally-motivated constitutive formulation…

生物物理 · 物理学 2018-01-18 D Pond , A McBride , L Davids , B D Reddy , G Limbert

We provide a numerical study of the macroscopic model of [3] derived from an agent-based model for a system of particles interacting through a dynamical network of links. Assuming that the network remodelling process is very fast, the…

Mechanical models of brain tissue are a beneficial tool to simulate neurosurgical interventions, disease progression, or brain development. However, the accuracy and predictive capacity of such a model relies on a precise experimental…

医学物理 · 物理学 2026-05-29 Laura Ruhland , Nina Reiter , Silvia Budday , Kai Willner

The theory of biochemical processes needs simple but realistic models of phenomena underlying microscopic dynamics of proteins. Many experiments performed in the 1980s have demonstrated that within the protein native state, apart from usual…

凝聚态物理 · 物理学 2007-05-23 Michal Kurzynski

Proteins constitute a large group of macromolecules with a multitude of functions for all living organisms. Proteins achieve this by adopting distinct three-dimensional structures encoded by the sequence of their constituent amino acids in…

统计方法学 · 统计学 2021-09-16 Mohammad Arashi , Najmeh Nakhaei Rad , Andriette Bekker , Wolf Dieter Schubert

We introduce and discuss a kinetic framework describing the time evolution of the statistical distributions of a population divided into the compartments of susceptible, infectious, recovered, and resistant in the presence of a microbial…

种群与进化 · 定量生物学 2026-05-07 Marco Menale , Giuseppe Toscani , Mattia Zanella

In this work we show how a network inspired by a coarse-grained description of actomyosin cytoskeleton can learn - in a contrastive learning framework - from environmental perturbations if it is endowed with mechanosensitive proteins and…

We model and simulate the stepping dynamics of the kinesin motor including electric and mechanical forces, environmental noise, and the complicated potentials produced by tracking and neighboring protofilaments. Our dynamical model supports…

生物物理 · 物理学 2016-05-02 Alexander I Nesterov , Gennady P Berman , Mónica F Ramírez

Generative machine learning models are increasingly being used to design novel proteins for therapeutic and biotechnological applications. However, the current methods mostly focus on the design of proteins with a fixed backbone structure,…

生物大分子 · 定量生物学 2025-03-04 Petr Kouba , Joan Planas-Iglesias , Jiri Damborsky , Jiri Sedlar , Stanislav Mazurenko , Josef Sivic

Collagen is a key structural protein in the human body, which undergoes mineralization during the formation of hard tissues. Earlier studies have described the mechanical behavior of bone at different scales highlighting material features…

应用物理 · 物理学 2021-07-02 Mario Milazzo , Gang Seob Jung , Serena Danti , Markus J. Buehler

Many aspects of the study of protein folding and dynamics have been affected by the recent advances in machine learning. Methods for the prediction of protein structures from their sequences are now heavily based on machine learning tools.…

生物物理 · 物理学 2019-11-25 Frank Noé , Gianni De Fabritiis , Cecilia Clementi

Sacrificial bonds and hidden length in structural molecules account for the greatly increased fracture toughness of biological materials compared to synthetic materials without such structural features, by providing a molecular-scale…

软凝聚态物质 · 物理学 2014-05-07 Charles K. C. Lieou , Ahmed E. Elbanna , Jean M. Carlson

We present a hidden Markov model that describes variation in an animal's position associated with varying levels of activity in action potential spike trains of individual place cell neurons. The model incorporates a coarse-graining of…

应用统计 · 统计学 2014-12-22 Marc Box , Matt W. Jones , Nick Whiteley

As a nonlocal extension of continuum mechanics, peridynamics has been widely and effectively applied in different fields where discontinuities in the field variables arise from an initially continuous body. An important component of the…

数值分析 · 数学 2021-09-22 Xiao Xu , Marta D'Elia , John T. Foster

High speed machining has been improved thanks to considerable advancement on the tools (optimum geometry, harder materials), on machined materials (increased workability and machining capacity for harder workpieces) and finally on the…

经典物理 · 物理学 2009-09-29 Olivier Cahuc , Alain Gérard

The cellular cytoskeleton is an active material, driven out of equilibrium by molecular motor proteins. It is not understood how the collective behaviors of cytoskeletal networks emerge from the properties of the network's constituent motor…

亚细胞过程 · 定量生物学 2017-12-19 Peter J. Foster , Wen Yan , Sebastian Fürthauer , Michael J. Shelley , Daniel J. Needleman

Fibrous networks such as collagen are common in physiological systems. One important function of these networks is to provide mechanical stability for cells and tissues. At physiological levels of connectivity, such networks would be…

软凝聚态物质 · 物理学 2021-08-09 Sadjad Arzash , Jordan L. Shivers , Fred C. MacKintosh