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Mathematics
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Computational Methods for Biological Modeling and Simulation
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Computational Methods for Biological Modeling and Simulation

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematical Biology".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 1709

Special Issue Editors

Dr. Dariusz Świetlik

E-Mail Website
Guest Editor
Division of Biostatistics and Neural Networks, Medical University of Gdańsk, Dębinki 1, 80-211 Gdańsk, Poland
Interests: biomedical modeling; artificial intelligence; bioinformaics; neural networks; computational neuroscience
Dr. Mariusz Baran

E-Mail Website
Guest Editor
Division of Biostatistics and Neural Networks, Medical University of Gdańsk, Dębinki 1, 80-211 Gdańsk, Poland
Interests: molecular modeling; molecular dynamics simulation; biological membranes; sterols; macrolide polyene antibiotics
Dr. Narcyz Knap

E-Mail Website
Guest Editor
Department of Medical Chemistry, Medical University of Gdańsk, Dębinki 1, 80-211 Gdańsk, Poland
Interests: medical chemistry; medical biochemistry; oxidative stress; computational chemistry

Special Issue Information

Dear Colleagues,

Artificial intelligence, computer simulation, and modeling are of great importance in understanding biological problems. Nowadays, artificial intelligence and mathematical modeling are becoming more important in biology and medicine.

This Special Issue aims to focus on the contributions of mathematical models in biological research.

This Special Issue seeks papers with novel ideas. By modeling or simulating intricate biological systems, articles should offer fresh biological, biochemical or medicinal insights. Studies that combine computational, theoretical, or both experimental and computational methods are invited. Studies describing integrative research in mathematics, statistics, medicine, and biological systems are also encouraged, as well as contributions that discuss cutting-edge computational, theoretical, and mathematical approaches to solving pertinent biological problems. Authors are invited to contribute to this Special Issue on many facets of artificial intelligence creation, study, and use in current biological and medical applications.

Dr. Dariusz Świetlik
Dr. Mariusz Baran
Dr. Narcyz Knap
Guest Editors

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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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

  • biological modeling
  • artificial intelligence
  • neural networks
  • computer simulation
  • machine learning
  • mathematical modeling for biological problems
  • biomathematics
  • deep learning
  • computational biology
  • simulation and modeling of biological systems
  • artificial intelligence applied to biological data
  • simulation methods in solving biological problems

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Published Papers (2 papers)

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22 pages, 7646 KiB  
Article
A Study on Effects of Species with the Adaptive Sex-Ratio on Bio-Community Based on Mechanism Analysis and ODE
by Haoyu Wang, Xiaoyuan Wan, Junyao Hou, Jing Lian and Yuzhao Wang
Mathematics 2024, 12(14), 2298; https://doi.org/10.3390/math12142298 - 22 Jul 2024
Viewed by 583
Abstract
The species of the adaptive male–female sex ratio has different effects on the bio-community. This paper is aimed at figuring out these effects through mechanism analysis and Ordinary Differential Equation (ODE). Hence, the ODE environmental model is created by combining the Lotka–Volterra model, [...] Read more.
The species of the adaptive male–female sex ratio has different effects on the bio-community. This paper is aimed at figuring out these effects through mechanism analysis and Ordinary Differential Equation (ODE). Hence, the ODE environmental model is created by combining the Lotka–Volterra model, the interspecific model, and other external factors. The stability is used to characterize these effects. According to this model, effects on bio-community stability under different male–female sex ratios are roughly observed. By innovatively considering different living environments during the species’ lifecycle, the ODE environmental model is optimized, and the effects of different male–female sex ratios on the bio-community are further analyzed by phase-track maps and relative standard deviation. It is found that there are different findings and features in resource-rich and resource-scarce living environments during the lifecycle. Meanwhile, bio-communities in these two types of environments are in a stable state based on different male–female sex ratios. Based on these findings, directive opinions can be used to manage and help relevant bio-communities. Full article
(This article belongs to the Special Issue Computational Methods for Biological Modeling and Simulation)
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21 pages, 4917 KiB  
Article
VSD: A Novel Method for Video Segmentation and Storage in DNA Using RS Code
by Jingwei Hong, Abdur Rasool, Shuo Wang, Djemel Ziou and Qingshan Jiang
Mathematics 2024, 12(8), 1235; https://doi.org/10.3390/math12081235 - 19 Apr 2024
Viewed by 688
Abstract
As data continue to grow in complexity and size, there is an imperative need for more efficient and robust storage solutions. DNA storage has emerged as a promising avenue to solve this problem, but existing approaches do not perform efficiently enough on video [...] Read more.
As data continue to grow in complexity and size, there is an imperative need for more efficient and robust storage solutions. DNA storage has emerged as a promising avenue to solve this problem, but existing approaches do not perform efficiently enough on video data, particularly for information density and time efficiency. This paper introduces VSD, a pioneering encoding method for video segmentation and storage in DNA, leveraging the Reed–Solomon (RS) error correction code. This method addresses these limitations through an innovative combination of segmentation and encoding, accompanied by RS coding to bolster error resilience. Additionally, the method ensures that the GC-content of the resultant DNA sequences remains around 50%, which further enhances the storage robustness. The experimental results demonstrate the method has commendable encoding efficiency and offers a solution to the prevailing issue of time inefficiency and error correction rates in DNA storage. This groundbreaking approach paves the way for the practical and reliable storage of large-scale video data in DNA, heralding a new era in the domain of information storage. Full article
(This article belongs to the Special Issue Computational Methods for Biological Modeling and Simulation)
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