Chaste: developing sustainable software for computational biology

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Gaining a full understanding of complex living systems is essential to tackling some of the most pressing research questions of the 21st Century, from the processes of early development of an organism to the effects of ageing. This system-level behaviour arises from complex interactions between component processes at many levels of biological organisation. For example, the development of a complex functional multicellular organism from a single cell involves tightly regulated and coordinated cell behaviours coupled through short- and long-range biochemical and mechanical signals.Recent advances in experimental techniques are resulting in a wealth of high-quality data and detailed, but isolated, descriptions of such complex biological systems. To truly comprehend this complexity, we need computational models, which can link observations to mechanisms in a quantitative, predictive, and experimentally verifiable way. The goal of this project is to produce high-quality software to support this, so that researchers can be sure that their computational models are generating the correct outputs reliably and reproducibly. Our software can then be used to guide the work of biologists in universities, research institutes and industry who are trying to understand how complex biological systems work.We have already started working towards this goal by developing Chaste, an open-source software library for modelling the behaviour of collections of cells in biological tissues. This involves multiscale modelling - that is combining mathematical models for things that happen in fractions of a second to processes that take years, as well as things that are very small (on the level of individual proteins) to the large scale of the whole body. To fulfil this software's full potential for the benefit of the UK biology research community, we will enable a richer variety of computational models to be simulated using the software, allowing researchers to utilise new high-quality 3D experimental data. We will also upgrade our software to make use of the latest advances in computing and hardware, and introduce new ways that users can interact and interface with the software without expert programming knowledge. In this way, we will accelerate the use of robust, extensible software for using computational models to help understand and interpret complex biological systems.