TY - JOUR T1 - The impact of mathematical modeling languages on model quality in systems biology: A software engineering perspective JF - bioRxiv DO - 10.1101/2019.12.16.875260 SP - 2019.12.16.875260 AU - Christopher Schölzel AU - Valeria Blesius AU - Gernot Ernst AU - Andreas Dominik Y1 - 2020/01/01 UR - http://biorxiv.org/content/early/2020/07/20/2019.12.16.875260.abstract N2 - Reproducible, understandable models that can be reused and combined to true multi-scale systems are required to solve the present and future challenges of systems biology. However, many mathematical models are still built for a single purpose and reusing them in a different context is challenging. These challenges are very similar to those faced in the engineering of large software systems. It is therefore likely that addressing model quality at the software engineering level will also be beneficial in systems biology. To do this, researchers cannot just rely on using an accepted standard language. They need to be aware of the characteristics that make this language desirable and they need guidelines how to utilize them to make their models more reproducible, understandable, reusable, and extensible. We therefore propose a list of desirable language characteristics and provide guidelines how to incorporate them in a model: In our opinion, a mathematical modeling language used in systems biology should be modular, human-readable, hybrid (i. e. support multiple formalisms), open, declarative, and allow to represent models graphically. We compare existing modeling languages with respect to these characteristics and show that there is no single best language but that trade-offs always have to be considered. We also illustrate the benefits of the individual language characteristics by translating a monolithic model of the human cardiac conduction system to a modular version using the modeling language Modelica as an example. Our experiment illustrates how each characteristic can have a substantial effect on the quality of the resulting model. When applied consistently, they can facilitate the creation of complex, multi-scale models. We therefore recommend to consider these criteria when choosing a programming language for any biological modeling task.Competing Interest StatementThe authors have declared no competing interest. ER -