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

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          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.

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          Most cited references73

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          A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs

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              Intestinal crypt homeostasis results from neutral competition between symmetrically dividing Lgr5 stem cells.

              Intestinal stem cells, characterized by high Lgr5 expression, reside between Paneth cells at the small intestinal crypt base and divide every day. We have carried out fate mapping of individual stem cells by generating a multicolor Cre-reporter. As a population, Lgr5(hi) stem cells persist life-long, yet crypts drift toward clonality within a period of 1-6 months. We have collected short- and long-term clonal tracing data of individual Lgr5(hi) cells. These reveal that most Lgr5(hi) cell divisions occur symmetrically and do not support a model in which two daughter cells resulting from an Lgr5(hi) cell division adopt divergent fates (i.e., one Lgr5(hi) cell and one transit-amplifying [TA] cell per division). The cellular dynamics are consistent with a model in which the resident stem cells double their numbers each day and stochastically adopt stem or TA fates. Quantitative analysis shows that stem cell turnover follows a pattern of neutral drift dynamics. Copyright © 2010 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                1553-734X
                1553-7358
                March 2013
                March 2013
                14 March 2013
                : 9
                : 3
                : e1002970
                Affiliations
                [1 ]Computational Biology, Department of Computer Science, University of Oxford, Oxford, United Kingdom
                [2 ]CoMPLEX, Maths & Physical Sciences, University College London, London, United Kingdom
                [3 ]Centre for Computational Science, University College London, London, United Kingdom
                [4 ]Department of Bioengineering, National University of Singapore, Singapore, Singapore
                [5 ]Oxford Centre for Collaborative Applied Mathematics, Mathematical Institute, University of Oxford, Oxford, United Kingdom
                [6 ]Computational Science Laboratory, Microsoft Research, Cambridge, United Kingdom
                [7 ]Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, United Kingdom
                [8 ]Department of Mathematics and Statistics, University of Saskatchewan, Saskatoon, Canada
                [9 ]Food and Drug Administration, Silver Spring, Maryland, United States of America
                [10 ]Fujitsu Laboratories of Europe, Hayes Park, London, United Kingdom
                [11 ]CARMEN project, INRIA Bordeaux Sud-Ouest, Talence, France
                UCSD, United States of America
                Author notes

                I have read the journal's policy and have the following conflicts: GRM and DJG have received research support from GlaxoSmithKline Plc.

                Designed and wrote the software: GRM CJA MOB RB JC AC YD SJD AGF DGH MEM JMO PP JPF JS NZ DJG. Conceived and designed the experiments: GRM YD AGF JMO DGH PP JPF. Performed the experiments: GRM AGF DGH JMO PP. Analyzed the data: GRM RB AGF JMO PP. Wrote the paper: GRM MOB RB JC YD SJD AGF PP JPF DJG.

                Article
                PCOMPBIOL-D-12-01337
                10.1371/journal.pcbi.1002970
                3597547
                23516352
                2c5ca78b-e2fd-494d-852f-ce5973589c04
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 22 August 2012
                : 20 January 2013
                Page count
                Pages: 8
                Funding
                This work was funded by: GlaxoSmithKline Grants and Affiliates Award to GRM and DJG; EPSRC e-Science pilot project in Integrative Biology (GR/S72023/01); EPSRC, Software for High Performance Computing project (EP/F011628/1); European Commission, Prediction of Drug Impact in Cardiac Toxicity (preDiCT), Framework 7 grant (DG-INFSO 224381); European Commission, Virtual Physiological Network of Excellence (VPH-NoE), Framework 7 grant (DG-INFSO 223920); 2020 Science: EPSRC and Microsoft Research, Cambridge through grant EP/I017909/1 ( www.2020science.net); BBSRC grant to Oxford Centre for Integrative Systems Biology (BB/D020190/1); The Life Sciences Interface and Systems Biology Doctoral Training Centres, and the Systems Approaches to Biomedical Science Industrial Doctorate Centre (EP/E501605/1, EP/G50029/1 and EP/G037280/1). This publication was also based on work supported in part by Award No. KUK-C1-013-04, made by King Abdullah University of Science and Technology (KAUST). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Computational Biology
                Biophysic Al Simulations
                Developmental Biology
                Pattern Formation
                Systems Biology
                Theoretical Biology
                Computer Science
                Computer Modeling
                Numerical Analysis
                Software Engineering
                Mathematics
                Applied Mathematics
                Finite Element Analysis
                Physics
                Biophysics
                Biophysics Simulations
                Cell Motility
                Interdisciplinary Physics

                Quantitative & Systems biology
                Quantitative & Systems biology

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