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.

UNLABELLED: In recent years there has been much development of the fundamental ideas underlying mathematical model curation in regard to models of biology. While much has been achieved in the realms of systems biology and bioinformatics, little progress has been made in relation to cellular electrophysiology modeling. The primary reason for slow progress in this field is the lack of a consistent and machine-readable reference description for a given model. CellML has been widely used to describe mathematical models of cellular electrophysiology in an unambiguous, machine-readable format. Through the use of well-annotated CellML models we propose a standard by which reference descriptions of cellular electrophysiology models can be similarly defined in an unambiguous, software independent, and machine-readable format. Adoption of this standard will provide a consistent technology by which cellular electrophysiology models can be curated. AVAILABILITY: http://www.bioeng.nus.edu.sg/compbiolab/p2/