@inbook{4431df60a7734a0a8e5d171e1a1ef378,
title = "The VPH-Physiome Project: standards, tools and databases for multi-scale physiological modelling: Standards, tools and databases for multi-scale physiological modelling",
abstract = "The VPH/Physiome project is developing tools and model databases for computational physiology based on three primary model encoding standards: CellML, SBML and FieldML. For the modelling community these standards are the equivalent of the DICOM standard for the clinical imaging community and it is important that the tools adhere to these standards to ensure that models from different groups can be curated, annotated, reused and combined. This chapter discusses the development and use of the VPH/Physiome standards, tools and databases, and also discusses the minimum information standards and ontology-based metadata standards that are complementary to the markup language standards. Data standards are not as well developed as the model encoding standards (with the DICOM standard for medical image encoding being the outstanding exception) but one new data standard being developed as part of the VPH/Physiome suite is BioSignalML and this is described here also. The PMR2 (Physiome Model Repository 2) database for CellML and FieldML files is also described, together with the Application Programming Interfaces (APIs) that facilitate access to the models from the visualisation (cmgui and GIMIAS) or computational (OpenCMISS, OpenCell/OpenCOR and other) software.",
author = "Peter Hunter and Chris Bradley and Randall Britten and David Brooks and Luigi Carotenuto and Richard Christie and Frangi, {Alejandro F} and Alan Garny and David Ladd and Caton Little and David Nickerson and Poul Nielsen and Andrew Miller and Xavier Planes and Martin Steghoffer and Alistair Young and Tommy Yu",
note = "Funding Information: This coordinates various US Governmental funding agencies involved in multi-scale bioengineering modelling research including NIH, NSF, NASA, the Dept of Energy (DoE), the Dept of Defense (DoD), the US Dept of Agriculture and the Dept of Veteran Affairs. See www.nibib.nih.gov/Research/MultiScaleModelling/IMAG . Funding Information: The Cardiac Atlas Project ( www.cardiacatlas.org ) is establishing a structural and functional atlas of the heart (Fonseca et al., 2011) combining cardiac modeling and biophysical analysis methods with a structural database for the comprehensive mapping of heart structure and function. Cardiac MRI examinations provide detailed, quantitative data on heart structure and function, and standardized protocols are now routinely used in a number of studies. Comprising cardiac magnetic resonance imaging (MRI) examinations, together with derived functional analyses and associated clinical variables, the Cardiac Atlas Project is developing a database, which will be extendible to allow inclusion of data from a variety of imaging and other sources. The initial goals of the project are to facilitate statistical analysis of regional heart shape and wall motion characteristics, across population groups, via the application of parametric mathematical modelling tools. Modelling tools and analysis methods developed by the University of Auckland are being combined with a database for neuroimaging and related clinical data and probabilistic mapping infrastructure developed by the UCLA Center for Computational Biology (CCB). The project is part of the National Centers for Biological Computing (NCBC) collaboration program and is funded by the US National Institutes of Health. The Cardiac Atlas Project aims to significantly improve the evaluation of cardiac performance and disease processes, establish characteristic parameters of cardiac structure and function on a regional basis, and enable the evaluation of clinical cases in relation to the statistical distributions within patient subgroups. Funding Information: CellML separates the syntax of a model (e.g. the mathematical equations encoded in MathML) from the semantics (the biological and biophysical meanings of the model components and parameters) defined in the model metadata by reference to suitable ontologies. In addition, models can be broken down into components; this facilitates building complex models by importing modular components defined in libraries. SBML is more closely tied to the concepts of biochemical and genetic networks, and does not maintain such a clear separation between the mathematical representation and the biological semantics. FieldML deals with the encoding of anatomy at multiple spatial scales by allowing hierarchies of material coordinate systems that preserve anatomical relationships (e.g. coronary arteries embedded in a deforming myocardial tissue that is itself part of a heart contained within a torso). These three standards are recommended both by the US National Institutes of Health (NIH) and by the European Commission for the VPH project. Funding Information: The development of standards, tools and databases for the VPH/Physiome project is being funded by many public good funding agencies in Europe (e.g. the EU ICT VPH 2, 4 & 6 calls and particularly the NoE and euHeart projects), the US (the MSM Physiome RFPs) and many other countries including the UK (especially the Wellcome Trust), Japan and New Zealand. The authors thank the many people from many different groups around the globe who have contributed to the infrastructure described here – for details see the websites given for the various software projects described in the document. Funding from the Wellcome Trust for the Heart Physiome Project and the European Union for the VPH Network of Excellence (VPH NoE FP7-ICT2008-223920) and the euHeart project (VPH euHeart FP7-ICT2008-224495) is gratefully acknowledged. ",
year = "2012",
doi = "10.1007/978-88-470-1935-5_8",
language = "English",
isbn = "9788847019348",
series = "Modeling, Simulation and Applications",
publisher = "Springer Berlin",
pages = "205--250",
editor = "D Ambrosi and A Quarteroni and G Rozza",
booktitle = "Modelling Physiological Flows",
address = "Germany",
}