Mathematics in Medical and Life Sciences

Open Source Software and Code in Mathematical Biology

Dear Colleagues,

The diversity and complexity of models and data analysis challenges in Mathematical Biology have long motivated the development of computational approaches, often involving bespoke numerical methods and software. These efforts range from small project-specific scripts to large-scale collaborative frameworks for models and data. Increasing complexity of biological data, integration of mechanical, biochemical, and multiscale effects, advances in algorithms and AI, and the growing sophistication of computer hardware all present both challenges and opportunities for researchers working with code and open-source software.

Yet barriers – both real and perceived – remain in communicating code-intensive research. On one hand, multidisciplinary and biomedical journals often prioritise novel biological results over methodological advances, particularly when techniques are refined or extended rather than entirely new. On the other hand, mathematical journals emphasise model formulation and analysis, while software-focused journals typically assess the quality of the software product rather than the underlying science. To address this gap, Mathematics in Medical and Life Sciences (MMLS) invites contributions that showcase the value of code and software in Mathematical Biology.

All submissions should meet the core MMLS criteria: relating to mathematical soundness, clarity and novelty in techniques and/or application, demonstrable relevance to current biology, ecology, or medicine, and conclusions clearly supported by the analysis. Within this remit, we strongly encourage submissions across the breadth of code and open-source software-based research in Mathematical Biology (hereafter referred to as ‘software’). Topics include, but are not limited to:

• Implementations of methods to address problems of broad relevance in Mathematical Biology and are not otherwise available.
• Software for solving complex integrated models (e.g. mechanical, stochastic, or biochemical effects) that cannot be handled by standard packages.
• Extensions or enhancements of established software projects that add new modelling or analysis capabilities.
• Comparative studies and benchmarking of software packages for accuracy and efficiency, or implementations of alternative conceptual frameworks (e.g. continuous versus discrete, stochastic versus deterministic).
• Approaches leveraging state-of-the-art computational architecture or paradigms.
• Parameter inference involving complex computational models or data.
• Software that broadens accessibility for domain scientists (e.g. in biology, medicine, or ecology), or translates mathematical models into practical predictive or analytical tools.

To maximise engagement, submissions to this special issue must meet three additional requirements:

1) Code should be provided in a form that can be compiled or executed using widely available free and open-source software or libraries.

2) While extensive documentation is not required, each script, function, or class should include a brief description of its role.

3) A runnable, repeatable, and minimal but non-trivial example should be included. This example should demonstrate the software’s use and highlight its potential.

Sincerely yours,

David J. Smith
Editor
Mathematics in Medical and Life Sciences

Peter Stewart
Section Editor
Mathematics in Medical and Life Sciences

Note
Mathematics in Medical and Life Sciences is an open access, international journal publishing original research and reviews in mathematics, statistics, computational biology and computational engineering with domain relevance to current questions and challenges at the cutting edges of medicine, biology or the life sciences.