Chaste: An Open Source C++ Library for Computational Physiology and Biology

Abstract

Chaste — Cancer, Heart And Soft Tissue Environment — is an open source C++ library for the computational simulation of mathematical models developed for physiology and biology. Code development has been driven by two initial applications: cardiac electrophysiology and cancer development. A large number of cardiac electrophysiology studies have been enabled and performed, including high-performance computational investigations of defibrillation on realistic human cardiac geometries. New models for the initiation and growth of tumours have been developed. In particular, cell-based simulations have provided novel insight into the role of stem cells in the colorectal crypt. Chaste is constantly evolving and is now being applied to a far wider range of problems. The code provides modules for handling common scientific computing components, such as meshes and solvers for ordinary and partial differential equations (ODEs/PDEs). Re-use of these components avoids the need for researchers to ‘re-invent the wheel’ with each new project, accelerating the rate of progress in new applications. Chaste is developed using industrially-derived techniques, in particular test-driven development, to ensure code quality, re-use and reliability. In this article we provide examples that illustrate the types of problems Chaste can be used to solve, which can be run on a desktop computer. We highlight some scientific studies that have used or are using Chaste, and the insights they have provided. The source code, both for specific releases and the development version, is available to download under an open source Berkeley Software Distribution (BSD) licence at http://www.cs.ox.ac.uk/chaste, together with details of a mailing list and links to documentation and tutorials.

Multiscale cardiac modelling reveals the origins of notched T waves in long QT syndrome type 2

“…However, because of the problem of computational load, it has not been possible to tackle this problem at the organ level. To overcome this hurdle, we developed a highly parallelized implementation of the Cancer, Heart and Soft Tissue Environment 30 utilizing General Purpose computing on GPUs (GPGPU). Parallel computing exploits the fact that a large problem can be subdivided into many smaller ones that are solved simultaneously, conventionally by distributing the sub-problems to CPU-processing 'cores' on interconnected computers.…”

Simulating tissue mechanics with agent-based models: concepts, perspectives and some novel results

“…Therefore, it is possible to perform large-scale parameter sweeps and sensitivity analyses with CPM-based models [128,129]. Furthermore, open source software CPM modeling is readily available [130][131][132] which makes it easy to implement and simulate models using the CPM. However, there are some major disadvantages to the CPM.…”

A computational model of nuclear self-organisation in syncytial embryos

“…As a result, the appropriate modelling framework is to use individual-based 'cell-centre' models consisting of particles interacting via position-dependent force laws, see e.g. Meineke et al (2001); Mirams et al (2013); Drasdo and Höhme (2005).…”

“…These range from simple linear spring-like force laws, e.g. Mirams et al (2013); Meineke et al (2001), to models that include cell-cell adhesion forces (Drasdo and Höhme (2005)) and more complex elastic interactions, e.g. interacting elastic spheres (Schaller and Meyer-Hermann (2005)).…”

“…To solve Eq. (3) the "PETSc" suite (Balay et al (2011(Balay et al ( , 2010(Balay et al ( , 1997) with an LU decomposition is used, the convex hull is calculated using "qhull" (Barber et al (1996)), and the cell cycle model is provided by "Chaste" (Mirams et al (2013); Pitt-Francis et al (2009)). …”