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Much of our mechanistic understanding of the functions of biological macromolecules is based on static structural experiments, which can be modelled either as single structures or conformational ensembles. While these provide us with…

Biomolecules · Quantitative Biology 2025-10-02 Daria Gusew , Carl G. Henning Hansen , Kresten Lindorff-Larsen

Simulations of knotting and unknotting in polymers or other filaments rely on random processes to facilitate topological changes. Here we introduce a method of \textit{topological steering} to determine the optimal pathway by which a…

Geometric Topology · Mathematics 2025-04-18 Agnese Barbensi , Alexander R. Klotz , Dimos Gkountaroulis

Computational models have become an essential part of exploratory protocols in cell biology, as a complement to in vivo or in vitro experiments. These virtual models have the twofold advantage of enabling access to new types of data and…

Medical Physics · Physics 2021-12-20 Maxime Vassaux , Laurent Pieuchot , Karine Anselme , Maxence Bigerelle , Jean-Louis Milan

A Topological examination of phospholipid dynamics in the Far from Equilibrium state has demonstrated that metabolically active cells use waste heat to generate spatially patterned membrane flows by forced convection and shear. This paper…

General Physics · Physics 2007-05-23 J T Lofthouse

The determination of the mobility of parallel mechanisms (PM) is a fundamental problem. An automatic and intelligent analysis platform will be a significant tool for the design and optimization of mechanical systems. Based on the theory of…

Robotics · Computer Science 2019-07-22 Xiaorong Zhu , Huiping Shen , Chengqi Wu , Damien Chablat , Tingli Yang

Understanding the dynamic behavior of biomolecules is fundamental to elucidating biological function and facilitating drug discovery. While Molecular Dynamics (MD) simulations provide a rigorous physical basis for studying these dynamics,…

Biomolecules · Quantitative Biology 2026-03-19 Liang Shi , Jiarui Lu , Junqi Liu , Chence Shi , Zhi Yang , Jian Tang

We use topological data analysis and machine learning to study a seminal model of collective motion in biology [D'Orsogna et al., Phys. Rev. Lett. 96 (2006)]. This model describes agents interacting nonlinearly via attractive-repulsive…

The development of chemical reaction models aids understanding and prediction in areas ranging from biology to electrochemistry and combustion. A systematic approach to building reaction network models uses observational data not only to…

Computational Engineering, Finance, and Science · Computer Science 2019-01-23 Nikhil Galagali , Youssef M. Marzouk

Spontaneous structural rearrangements play a central role in the organization and function of complex biomolecular systems. In principle, physics-based computer simulations like Molecular Dynamics (MD) enable us to investigate these…

Quantum Physics · Physics 2026-03-19 Danial Ghamari , Philipp Hauke , Roberto Covino , Pietro Faccioli

Topology optimization (TO) is a family of computational methods that derive near-optimal geometries from formal problem descriptions. Despite their success, established TO methods are limited to generating single solutions, restricting the…

Machine Learning · Computer Science 2025-06-18 Andreas Radler , Eric Volkmann , Johannes Brandstetter , Arturs Berzins

The interaction between proteins and DNA is a key driving force in a significant number of biological processes such as transcriptional regulation, repair, recombination, splicing, and DNA modification. The identification of DNA-binding…

Quantitative Methods · Quantitative Biology 2017-05-10 Hamid Reza Hassanzadeh , Pushkar Kolhe , Charles L. Isbell , May D. Wang

Reliable identification of molecular biomarkers is essential for accurate patient stratification. While state-of-the-art machine learning approaches for sample classification continue to push boundaries in terms of performance, most of…

Molecular Networks · Quantitative Biology 2019-11-07 Matteo Manica , Joris Cadow , Roland Mathis , María Rodríguez Martínez

A steadily growing computational power is employed to perform molecular dynamics simulations of biological macromolecules, which represents at the same time an immense opportunity and a formidable challenge. In fact, large amounts of data…

Soft Condensed Matter · Physics 2022-05-18 Margherita Mele , Roberto Covino , Raffaello Potestio

Molecular docking is an essential tool for drug design. It helps the scientist to rapidly know if two molecules, respectively called ligand and receptor, can be combined together to obtain a stable complex. We propose a new multi-objective…

Quantitative Methods · Quantitative Biology 2008-11-05 Jean-Charles Boisson , Laetitia Jourdan , El-Ghazali Talbi , Dragos Horvath

Disentangling the mechanistic details of a chemical reaction pathway is a hard problem that often requires a considerable amount of chemical intuition and a component of luck. Experiments struggle in observing short-life metastable…

Chemical Physics · Physics 2019-08-01 Valerio Rizzi , Dan Mendels , Emilia Sicilia , Michele Parrinello

To facilitate rational molecular and materials design, this research proposes an integrated computational framework that combines stochastic simulation, ab initio quantum chemistry, and molecular docking. The suggested workflow allows…

Materials Science · Physics 2026-01-08 Md Rakibul Karim Akanda , Michael P. Richard

We present a kinetic Monte Carlo method for simulating chemical transformations specified by reaction rules, which can be viewed as generators of chemical reactions, or equivalently, definitions of reaction classes. A rule identifies the…

Quantitative Methods · Quantitative Biology 2010-07-09 Jin Yang , Michael I. Monine , James R. Faeder , William S. Hlavacek

There are many problems in biochemistry that are difficult to study experimentally. Simulation methods are appealing due to direct availability of atomic coordinates as a function of time. However, direct molecular simulations are…

Biomolecules · Quantitative Biology 2023-05-24 Malin Luking , David van der Spoel , Johan Elf , Gareth A. Tribello

One of the significant steps in the process leading to the identification of proteins is mass spectrometry, which allows for obtaining information about the structure of proteins. Removing isotope peaks from the mass spectrum is vital and…

Machine Learning · Statistics 2023-02-16 Anna Glodek , Joanna Polańska , Marta Gawin

The output of molecular dynamics simulations is high-dimensional, and the degrees of freedom among the atoms are related in intricate ways. Therefore, a variety of analysis frameworks have been introduced in order to distill complex motions…

Biomolecules · Quantitative Biology 2019-08-06 Brooke E. Husic , Frank Noé
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