Symmetry in Computational Mathematics and Biophysics

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Mathematics".

Deadline for manuscript submissions: 17 June 2024 | Viewed by 2863

Special Issue Editor

Department of Mathematics, West Chester University of Pennsylvania, West Chester, PA 19383, USA
Interests: scientfic (parallel) computing algrithms; numerical methods for solving ordinary and partial differential equation models; interface problems; bioheat equations; cardiac physiology

Special Issue Information

Dear Colleagues,

As a part of the journal Symmetry, whose scope covers theories and applications related to symmetry/asymmetry phenomena in all multidisciplinary studies, this Special Issue is dedicated to demonstrating the strong bond between two research fields, Computational Mathematics and Biophysics, and showcasing the most recently developed mathematical models, numerical methods, and computing algorithms to address questions arising in the field of Biophysics.

Currently, many state-of-art models do not have exact solutions in closed forms due to their complexity. In Biophysics, such models include, but are not limited to, differential equation models in Molecular Biology, Cardia Physiology, Thermal Science, etc. With the rapid advances in modern computer technology, numerical methods have played an important role and become a vital approach to solve those models for accurate approximations of exact solutions. Such numerical methods include, but are not limited to, finite difference methods, finite volume methods, finite element methods, etc. In addition, (parallel) computing algorithms, which are developed to utilize the computing power of modern high-performance computing cluster to accelerate the calculations for solving large-scale problems in Biophysics, have received much attention and naturally fall in the scope of this Special Issue. Original works in all aforementioned areas are welcome in this Special Issue.

We appreciate your consideration to publish your work in this Special Issue.

Submit your paper and select the Journal “Symmetry” and the Special Issue “Symmetry in Computational Mathematics and Biophysics” via: MDPI submission system. Our papers will be published on a rolling basis and we will be pleased to receive your submission once you have finished it.

Dr. Chuan Li
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biophysics
  • mathematical biology
  • computational mathematics
  • mathematical modeling
  • numerical methods for solving ordinary and partial differential equations
  • computing algorithms

Published Papers (2 papers)

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Research

13 pages, 549 KiB  
Article
Analytical Decomposition of Transition Flux to Cycle Durations via Integration of Transition Times
by Ruizheng Hou
Symmetry 2022, 14(9), 1857; https://doi.org/10.3390/sym14091857 - 06 Sep 2022
Viewed by 902
Abstract
Rigorous methods of decomposing kinetic networks to cycles are available, but the solutions usually contain entangled transition rates, which are difficult to analyze. This study proposes a new method of decomposing net transition flux to cycle durations, and the duration of each cycle [...] Read more.
Rigorous methods of decomposing kinetic networks to cycles are available, but the solutions usually contain entangled transition rates, which are difficult to analyze. This study proposes a new method of decomposing net transition flux to cycle durations, and the duration of each cycle is an integration of the transition times along the cycle. The method provides a series of neat dependences from the basic kinetic variables to the final flux, which support direct analysis based on the formulas. An assisting transformation diagram from symmetric conductivity to asymmetric conductivity is provided, which largely simplifies the application of the method. The method is likely a useful analytical tool for many studies relevant to kinetics and networks. Applications of the method shall provide new kinetic and thermodynamic information for the studied system. Full article
(This article belongs to the Special Issue Symmetry in Computational Mathematics and Biophysics)
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14 pages, 2585 KiB  
Article
The Mechanistic Integration and Thermodynamic Optimality of a Nanomotor
by Ruizheng Hou
Symmetry 2022, 14(2), 416; https://doi.org/10.3390/sym14020416 - 19 Feb 2022
Cited by 1 | Viewed by 1011
Abstract
The performance of artificial nanomotors is still far behind nature-made biomolecular motors. A mechanistic disparity between the two categories exists: artificial motors often rely on a single mechanism to rectify directional motion, but biomotors integrate multiple mechanisms for better performance. This study proposes [...] Read more.
The performance of artificial nanomotors is still far behind nature-made biomolecular motors. A mechanistic disparity between the two categories exists: artificial motors often rely on a single mechanism to rectify directional motion, but biomotors integrate multiple mechanisms for better performance. This study proposes a design for a motor-track system and shows that by introducing asymmetric compound foot-track interactions, both selective foot detachment and biased foot-track binding arise from the mechanics of the system. The two mechanisms are naturally integrated to promote the motility of the motor towards being unidirectional, while each mechanism alone only achieves 50% directional fidelity at most. Based on a reported theory, the optimization of the motor is conducted via maximizing the directional fidelity. Along the optimization, the directional fidelity of the motor is raised by parameters that concentrate more energy on driving selective-foot detachment and biased binding, which in turn promotes work production due to the two energies converting to work via a load attached. However, the speed of the motor can drop significantly after the optimization because of energetic competition between speed and directional fidelity, which causes a speed-directional fidelity tradeoff. As a case study, these results test thermodynamic correlation between the performances of a motor and suggest that directional fidelity is an important quantity for motor optimization. Full article
(This article belongs to the Special Issue Symmetry in Computational Mathematics and Biophysics)
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