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Advanced Applications of Partial Differential Equations in Mathematical Biology

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "C1: Difference and Differential Equations".

Deadline for manuscript submissions: closed (31 October 2025) | Viewed by 528

Special Issue Editors


E-Mail Website
Guest Editor
College of Future Tech, Northwestern Polytechnical University, Xi’an, China
Interests: partial differential equations
School of Mathematics and Statistics, University of Glasgow, Glasgow, UK
Interests: soft tissue mechanics (constitutive modelling, constrained mixture theory); personalized cardiac modelling; fluid-structure interaction and machine learning-based surrogate models

Special Issue Information

Dear Colleagues,

Partial Differential Equations (PDEs) play a pivotal role in advancing our understanding of complex biological systems by providing a robust framework to describe spatial and temporal dynamics, with wide applications from cellular dynamics to organ-level mechanics. This Special Issue will focus on various applications of PDEs to important biological problems, highlighting novel mathematical models, cutting-edge computational methods, theoretical and analytical approaches, and the integrating of artificial intelligence. We invite researchers to submit original research work as well as review articles on the application of PDEs to mathematical biology. Potential topics include, but are not limited to, the following:

  • Advances in mathematical models of various biological systems using partial/ordinary differential equations;
  • Stability analysis, i.e. bifurcations, chaos, etc.;
  • Multiscale and multiphysics large-scale modelling;
  • Reduced-order models of complex physiological systems;
  • Numerical methods for solving complex PDE systems;
  • Integrating artificial intelligence with PDE, i.e., physics-informed neural networks.

Prof. Dr. Li Cai
Dr. Hao Gao
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 250 words) can be sent to the Editorial Office for assessment.

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

  • mathematical biology
  • stability analysis
  • theoretical solution
  • numerical methods
  • artificial intelligence

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Published Papers (1 paper)

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Research

21 pages, 6915 KB  
Article
Spatiotemporal Pattern Selection in a Modified Leslie–Gower Predator–Prey System with Fear Effect and Self-Diffusion
by Xintian Jia, Lingling Zhao, Lijuan Zhang and Kunlun Huang
Mathematics 2026, 14(1), 190; https://doi.org/10.3390/math14010190 - 4 Jan 2026
Viewed by 213
Abstract
Indirect fear effects profoundly influence predator–prey dynamics by reducing prey reproduction. Whereas previous studies have investigated fear effects or self-diffusion separately in Leslie–Gower models, the novelty of this work lies in their simultaneous incorporation into a modified Leslie–Gower predator–prey system with Allee effect, [...] Read more.
Indirect fear effects profoundly influence predator–prey dynamics by reducing prey reproduction. Whereas previous studies have investigated fear effects or self-diffusion separately in Leslie–Gower models, the novelty of this work lies in their simultaneous incorporation into a modified Leslie–Gower predator–prey system with Allee effect, leading to previously unreported bifurcations and spatiotemporal pattern selection. The temporal system exhibits up to six equilibria and undergoes a codimension-2 Bogdanov–Takens bifurcation. In the spatial extension, Turing instability is triggered when the predator diffusion coefficient exceeds a critical threshold. Using weak nonlinear multiple-scale analysis, amplitude equations are derived, and their stability analysis classifies stationary patterns into spots, stripes, and spot–stripe mixtures depending on the distance from the Turing onset. Numerical simulations confirm that low, moderate, and high predator diffusivity, respectively, favour spotted, mixed, and striped prey distributions. These results emphasise the critical role of fear-mediated indirect interactions and diffusion in driving spatial heterogeneity and ecosystem stability. Full article
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