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 visualization (cmgui and GIMIAS) or computational (OpenCMISS, OpenCell/OpenCOR and other) software.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
The concept of a “Physiome Project” was presented in a report from the Commission on Bioengineering in Physiology to the International Union of Physiological Sciences (IUPS) Council at the 32nd World Congress in Glasgow in 1993. The term “physiome” comes from “physio” (life) + “ome” (as a whole), and is intended to provide a “quantitative description of physiological dynamics and functional behaviour of the intact organism” [2, 3, 4]. A satellite workshop “On designing the Physiome Project”, organized and chaired by the Chair of the IUPS ‘Commission on Bioengineering in Physiology’ (Prof Jim Bassingthwaighte), was held in Petrodvoretz, Russia, following the 33 rd World Congress in St Petersburg in 1997. A symposium on the Physiome Project was held at the 34th World Congress of IUPS in Christchurch, New Zealand, in August 2001 and the Physiome Project was designated by the IUPS executive as a major focus for IUPS during the next decade.
- 2.
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.
- 3.
The STEP (“Strategy for a European Physiome”) report is available at www.europhysiome. org/roadmap
- 4.
See www.vph-noe.eu for details on the 15 projects funded under the VPH calls.
- 5.
See www.physiome.jp for details on the Japanese Physiome Project.
- 6.
- 7.
- 8.
- 9.
- 10.
Interface Description Language. See www.OMG.org/cgi-bin/doc?formal/02-06-39
- 11.
Distributed under a tri-licence MPL, GPL or LGPL.
- 12.
Distributed under a tri-license MPL, GPL or LGPL. See also 7.
- 13.
GIMIAS is released under a BSD license.
- 14.
- 15.
All software components developed by the CAP are open source and are freely available under the Mozilla Public License Version 1.1 (mozilla.org/MPL/MPL-1.1.txt).
References
Aspell M.: Professional Plone Development. Packt Publishing, 2007.
Beard D.A.: A biophysical model of the mitochondrial respiratory system and oxidative phosphorylation. PLoS. Comp. Biol. 1(4), 2005.
Beard D.A., Britten R., Cooling M.T, Garny A., Halstead M.D.B., Hunter P.J., Lawson J, Lloyd C.M., Marsh J., Miller A., Nickerson D.P., Nielsen P.M.F., Nomura T., Subramanium S., Wimalaratne S.M., Yu T.: CellML metadata: Standards, associated tools and repositories. Philosophical Transactions of the Royal Society A367(1895): 1845–1867, 2009.
Bradley C.P., Pullan A.J., Hunter P.J.: Geometric modelling of the human torso using cubic Hermite elements. Annals of Biomedical Engineering 25(1): 96–111, 1997.
Bradley et al.: OpenCMISS: A multi-physics & multi-scale computational infrastructure for the VPH/Physiome project. Progress in Biophysics and Molecular Biology, In press 2011.
Carroll J.J., Bizer C., Hayes P., Stickler P.: Named graphs, provenance and trust, In: Proceedings of the 14th International Conference on World Wide Web, ser. WWW ’05. New York, NY, USA: ACM, pp. 613–622, 2005.
Christie G.R., Blackett S.A., Hunter P.J., Bullivant D.P.: Modelling and visualising the heart. Computing and Visualisation in Science 4: 227–235, 2002.
Christie G.R., Nielsen P.M.F., Blackett S.A., Bradley C.P., Hunter P.J.: FieldML: Standards, tools and repositories. Phil. Trans. Roy. Soc. A 367: 1869–1884, 2009.
Cooling M., Hunter P.J., Crampin E.J.: Modelling hypertrophic IP3 transients in the cardiac myocyte. Biophys. J. 93: 3421–3433, 2007.
Cuellar A.A., Lloyd C.M., Nielsen P.F., Bullivant D.P., Nickerson D.P., Hunter P.J.: An overview of CellML 1.1, a biological model description language. SIMULATION: Transactions of The Society for Modelling and Simulation International 79(12): 740–747, 2003.
Folk M., Cheng A., Yates K.: HDF5: A file format and I/O library for high performance computing applications. In Proceedings of Supercomputing’99 (CD-ROM), 1999.
Fonseca C.G., Backhaus M., Bluemke D.A., Britten R.D., Chung J.D., Cowan B.R., Dinov I.D., Finn J.P., Hunter P.J., Kadish A.H., Lee D.C., Lima J.A.C., Medrano-Gracia P., Shivkumar K., Tao W., Young A.A.: The Cardiac Atlas Project – An imaging database for computational modelling and statistical atlases of the heart. Bioinformatics, in press 2011.
Gamma E., Helm R., Johnson R., Vlissides J.: Design patterns: Elements of reusable objectoriented software. Addison-Wesley, Reading, MA, 1995.
Garny A., Nickerson D., Cooper J., Weber dos Santos R., McKeever S., Nielsen P., Hunter P.: CellML and associated tools and techniques. Phil. Trans. Roy. Soc. A 366: 3017–3043, 2008.
Hinch R., Greenstein J.R., Tanskanen A.J. et al.: A simplified local control model of calciuminduced calcium release in cardiac ventricular myocytes. Biophys. J. 87: 3723–3736, 2004.
Hooks D.A., Tomlinson K.A., Marsden S.G. et al.: Cardiac microstructure: Implications for electrical propagation and defibrillation in the heart. Circ. Res. 9: 331–338, 2002.
Hunter P.J.: Modelling living systems: The IUPS/EMBS Physiome Project. Proceedings of the IEEE 94: 678–691, 2006.
Hunter P.J.: The IUPS Physiome Project: a framework for computational physiology. Progress in Biophysics and Molecular Biology 85(2–3): 551–569, 2004.
Hunter P.J., Borg T.K.: Integration from proteins to organs: The Physiome Project. Nature Reviews Molecular and Cell Biology 4, 237–243, 2003.
Hunter P.J., Nielsen P.M.F.: A strategy for integrative computational physiology. Physiology 20: 316–325, 2005.
Hunter P.J., Pullan A.J., Smaill B.H.: Modelling total heart function. Ann Review of Biomedical Engineering 5: 147–177, 2003.
Hunter P.J., Smaill B.H.: The analysis of cardiac function: a continuum approach. Prog. Biophys. Molec. Biol. 52: 101–164, 1989.
Hunter P.J., Viceconti M.: The VPH-Physiome Project: Standards and tools for multi-scale modelling in clinical applications. IEEE Reviews in Biomedical Engineering 2: 40–53, 2009.
Kemp B., Olivan J.: European data format ‘plus’(EDF+), an EDF alike standard format for the exchange of physiological data. Clinical Neurophysiology 114(9): 1755–1761, 2003.
Kereiakes D.J.: Interpreting the COURAGE trial. PCI is no better than medical therapy for stable angina? Seeing is not believing. Cleve. Clin. J. Med. 74(9): 637–8, 640–2, 2007.
Kohl P.: Bollensdorff C.: Garny A.: Effects of mechanosensitive ion channels on ventricular electrophysiology: experimental and theoretical models. Exp. Physiol. 91(2): 307–321, 2006.
LeGrice I.J., Hunter P.J., Smaill B.H.: Laminar structure of the heart: a mathematical model. Am. J. Physiol. 272: H2466–H2476, 1997.
LeGrice I.J., Smaill B.H., Chai L.Z. et al.: Laminar structure of the heart: ventricular myocyte arrangement and connective tissue architecture in the dog. Am. J. Physiol. 269: H571–H582, 1995.
Livshitz L.M., Rudy Y.: Regulation of Ca2+ and electrical alternans in cardiac myocytes: role of CAMKII and repolarizing currents. AJP: Heart and Circulatory Physiology 292: H2854–H2866, 2007.
Lloyd C.M., Halstead M.D.B., Nielsen P.M.F.: CellML: its future, present and past. Prog. Biophys. Mol. Biol. 85: 433–450, 2004.
Lloyd C.M., Lawson J.R., Hunter P.J., Nielsen P.F.: The CellML Model Repository. Bioinformatics 24(18): 2122–2123, 2008.
Miller A.K., Marsh J., Reeve A., Garny A., Britten R., Halstead M., Cooper J., Nickerson D.P., Nielsen P.M.F.: An overview of the CellML API and its implementation. BMCBioinformatics 11: 178, 2010.
Moody G.B.: WFDB Applications Guide, 10th edition, physionet.org/physiotools/wag/wag.htm, 2011.
Nash M.P., Hunter P.J.: Computational mechanics of the heart. J. Elasticity 61(1–3): 113–141, 2001.
Nickerson D.P., Hunter P.J.: The Noble cardiac ventricular electrophysiology models in CellML. Prog. Biophys. Molec. Biol. 90: 346–359, 2006.
Nickerson D.P., Terkildsen J., Hamilton K.L., Hunter P.J.: A tool for multi-scale modeling of the renal nephron. Interface Focus 1: 417–425, 2011.
Niederer S.A., Hunter P.J., Smith N.P.: A quantitative analysis of cardiac myocyte relaxation: a simulation study. Biophys. J. 90(5): 1697–722, 2006.
Nordsletten D.A., Hunter P.J., Smith N.P.: Conservative arbitrary lagrangian-eulerian forms for boundary driven and ventricular flows. Int. J. Num. Meth. Fluids 56(8): 1457–1463, 2007.
Nørager S., Iakovidis I., Cabrera M., Özcivelek R. (eds.): Towards virtual physiological human: multilevel modelling and simulation of the human anatomy and physiology – White Paper Edited by DG INFSO & DG JRC, Nov 2005. http://ec.europa.eu/information society/activities/health/docs/events/barcelona2005/ec-vph-white-paper2005nov.pdf.
Pandit S.V., Clark R.B., Giles W.R. et al.: A mathematical model of action potential heterogeneity in adult rat left ventricular myocytes. Biophys. J. 81(6): 3029–3051, 2001.
Saucerman J.J., McCulloch A.D.: Mechanistic systems models of cell signalling networks: a case study of myocyte adrenergic regulation. Prog. Biophys. and Mol. Biol. 11: 369–391, 2000.
Saucerman J.J., Brunton L.L., Michailova A.P., McCulloch A.D.: Modeling beta-adrenergic control of cardiac myocyte contractility in silico. Journal of Biological Chemistry 48: 47997–48003, 2003.
Savio-Galimberti E., Frank J., Inoue M., Goldhaber J.I., Cannell M.B., Bridge J.H., Sachse F.B.: Novel features of the rabbit transverse tubular system revealed by quantitative analysis of three-dimensional reconstructions from confocal images. Biophys. J. 95(4): 2053–2062, 2008.
Schlögl A.: Dataformats supported by BioSig biosig.sf.net, pub.ist.ac.at/?schloegl/biosig/TESTED 2008.
Schlögl A.: An overview on data formats for biomedical signals. In Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics, ser. IFMBE Proceedings, Dössel O. and Schlegel A. (eds.), World Congress on Medical Physics and Biomedical Engineering, Springer, 25/4: 1557–1560, 2009.
Schneider R.: About libRASCH. www.librasch.org/librasch/, 2007.
Smith N.P., Nickerson D.P., Crampin E.J., Hunter P.J.: Multiscale computational modeling of the heart. Acta Numerica 13: 371–431, 2004.
Smith N.P., Pullan A.J., Hunter P.J.: An anatomically based model of coronary blood flow and myocardial mechanics. SIAM J. Appl. Maths. 62: 990–1018, 2002.
ten Tusscher K.H.W.J., Noble D., Noble P.J., Panfilov A.V.: A model for human ventricular tissue, American Journal of Physiology 286: H1573–H1589, 2004.
Terkildsen J.R., Niederer S., Crampin E.J., Hunter P.J. Smith N.P.: Using Physiome standards to couple cellular functions for cardiac excitationcontraction. Exp. Physiol. 93: 919–929, 2008.
Acknowledgements
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.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Italia
About this chapter
Cite this chapter
Hunter, P. et al. (2012). The VPH-Physiome Project: Standards, tools and databases for multi-scale physiological modelling. In: Ambrosi, D., Quarteroni, A., Rozza, G. (eds) Modeling of Physiological Flows. MS&A — Modeling, Simulation and Applications, vol 5. Springer, Milano. https://doi.org/10.1007/978-88-470-1935-5_8
Download citation
DOI: https://doi.org/10.1007/978-88-470-1935-5_8
Publisher Name: Springer, Milano
Print ISBN: 978-88-470-1934-8
Online ISBN: 978-88-470-1935-5
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)