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Countering reproducibility issues in mathematical models with software engineering techniques: A case study using a
Christopher Schölzel1,2, Valeria Blesius1,2, Gernot Ernst3,4
1Technische Hochschule Mittelhessen-THM University of Applied Sciences, Giessen, Germany.
Plos One
|July 19, 2021
Summary
Reproducibility in systems biology is challenging. Applying software engineering best practices to mathematical models improves model understanding, debugging, and ensures reliable results.
Area of Science:
- Systems Biology
- Computational Biology
- Software Engineering
Background:
- In silico experiments in systems biology are assumed to be reproducible due to controlled environments.
- However, studies reveal that only about half of published mathematical models are reproducible without significant effort.
- This highlights a critical gap in the reliability of computational biological research.
Purpose of the Study:
- To investigate the causes of poor reproducibility in published mathematical models of biological systems.
- To demonstrate how software engineering techniques can enhance the reproducibility of these models.
- To present a case study of reimplementing a model of the atrioventricular node.
Main Methods:
- Examined a one-dimensional mathematical model of the atrioventricular node, identifying reproducibility barriers.
- Applied software engineering principles like unit testing, version control, and continuous integration.
- Reimplemented the model using the Modelica language, ensuring a robust and documented workflow.
- Utilized automated testing in a virtual machine for guaranteed methods reproducibility.
Main Results:
- Identified key issues hindering reproducibility: missing information, equation/parameter errors, lack of data/code, and incomplete protocols.
- The reimplemented Modelica model demonstrated improved understandability and facilitated easier debugging.
- The new workflow ensured methods reproducibility through automated testing and facilitated results reproducibility via published code, protocols, and data.
Conclusions:
- Rigorous application of software engineering practices is essential for overcoming reproducibility challenges in systems biology modeling.
- These practices lead to more understandable, maintainable, and verifiable computational models.
- The benefits extend beyond reproducibility, improving the efficiency and reliability of the model development process.
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