Methodological developments in systems biology

The field of systems biology has made significant progress in recent years, with advances in computational and experimental techniques enabling researchers to study biological systems in unprecedented detail. Furthermore, recent developments in the field have shown that systems biology-based approaches can provide an unprecedented trove of data for the early detection of disease transitions, the prediction of therapeutic responses and clinical outcomes, and the design of personalised treatments.

We invite submissions that focus on the latest developments in systems biology research methodology and its application in basic and translational research. Specifically, we encourage submissions on the following topics of interests but are not limited to:

• Novel computational methods for modelling and analysis of biological systems, in particular the development of computational frameworks that integrate deep learning with ODE or PDE models to provide efficient mechanisms for model fitting and prediction.
• Combining different computational methods and approaches to investigate mechanisms underlying emergent properties of biological systems, such as ODE with agent-based models or Boolean with genome-scale metabolic models.
• Classical mechanistic modelling, such as ODE, PDE, agent-based models, and Boolean, as applied to research in human disease, the microbiome, and plant biology.
• Network-based models, such as Petri-net and graph modelling, that integrate multi-omics data sets into computational models to study biological mechanisms, drug response, and personalised medicine.
• Single-cell modelling, which covers all areas of computational biology related to biological behaviour at the single-cell level, including stochastic dynamics, gene regulation, spatiotemporal dynamics, and a better understanding of cell self-organisation and cell response to stimuli.
• Multi-scale modelling addresses multiscale questions in biology through the integration of models and quantitative experiments, especially models that capture cellular dynamics and regulation, with an emphasis on the role played by the spatial organisation of its components.