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with explanations of the rules combined with examples of their usage. Keywords: computational physiology; modularity; physiome project; reproducibility; reusability. *Corresponding author: David P. Nickerson, University of Auckland, Auckland, New Zealand, E-mail: d.nickerson@auckland.ac.nz. https://orcid.org/0000-0003-4667-9779 Michael Clerx: University of Oxford, Oxford, UK. https://orcid.org/0000-0003-4062-3061 Michael T. Cooling, Alan Garny, Keri Moyle, Poul M. F. Nielsen and Hugh Sorby: University of Auckland, Auckland, New Zealand. https://orcid.org/0000

. Literatur Baureithel, U., und A. Bergmann: Herzloser Tod. Das Dilem- ma der Organspende. Klett-Cotta, Stuttgart (1999). Chinese Visible Human Project, Internetaddresse: http:// www.chinesevisiblehuman.com/index-e.asp Deuflhard, P.: Therapieplanung an virtuellen Krebspatienten. In: M. Aigner, E. Behrends (eds.): Alles Mathematik. Von Py- thagoras zum CD-Player. Vieweg Verlag, pp. 22–30 (2000). Human Rights Watch/Asia. Vol 6, no 9, S. 2. New York 1994. Hunter. P.J., and T.K. Borg: Integration from proteins to or- gans: the Physiome Project. Nature Rev., Molecular Cell Bio

, but it is located on an entirely different conceptual level: the ‘‘Physiome Project’’ comprises a large number of models on different scales and with varying complexity in the form of an open scientific platform. Model types Fluid dynamic models with lumped parameters Understanding the flow of blood and the propagation of pressure/flow waves through elastic tubes, the vessels, is fundamentally important to the comprehension of the blood circulation in the human body. For Newtonian flu- ids, flow is described by a set of nonlinear partial differ- ential equations

- malised way. Model repositories like JWS Online [6] or the BioMod- els Database [2] and standards like SBML [19] and CellML [26] show that this has been recognised in the scientific community. The Physiome Project, which itself claims to be the successor of the Human Genome Project, aims to serve as an integra- tion platform for all the different initiatives in this area [7; 11]. How realistic is the aim of a “vir- tual human”? Despite success stories like the “virtual heart” it is question- able whether it is possible to “glue” al the different models over all the

possible to the real processes in the human body. Most often physiological processes can be described by coupled differential equations – the reason might be that in fact coupled control loops take care of the steady function of the human body. Sometimes it is the rate constants within these equations that have to be measured in experiments, sometimes we need coefficients like diffusion constants in partial differential equations. The so-called “Physiome Project” supported by the International Union of Physi- ological Sciences aims at a complete set of equations and

above, it is not surprising that the mathematical and computational techniques used for molecular-scale systems-modelling are less appropriate. Bioengineers have used well established techniques, such as Finite Element Analysis, to define cells or zones of tissue and their interactions. This is best exemplified by the Physiome Project (6). Boundary Element analysis is a similar modelling technique but pays specific attention to the interfaces between elements (1), and several computational physiology groups have applied Computational Fluid Dynamics to

Krebspatienten. In: M. Aigner, E. Behrends (eds.): Alles Mathematik. Von Py- thagoras zum CD-Player. Vieweg Verlag, pp. 22–30 (2000). Human Rights Watch/Asia. Vol 6, no 9, S. 2. New York 1994. Hunter. P.J., and T.K. Borg: Integration from proteins to or- gans: the Physiome Project. Nature Rev., Molecular Cell Bio- logy, vol. 4, p. 237–243 (2003). Marcuse, H.: Der eindimensionale Mensch.. München 1998. Natterer, F.: The Mathematics of Computerized Tomography. New York/Stuttgart 1986. Visible Korean Human: I http://vkh3.kordic.re.kr/ Wadman, M.: Ethics worries over execution

: Computing and Visualization in Science, 12:201–205, 2009. [7] Ethier, M. and Bourgault, Y.: Semi-Implicit Time-Discretization Schemes for the Bidomain Model. In: SIAM J Numer Anal, 46(5):2443–2468, 1998. [8] Fink, M., Niederer, S. A., Cherry, E. M., Fenton, F. H., Koivumä- ki, J. T., Seemann, G., Thul, R., Zhang, H., Sachse, F. B., Beard, D., Crampin, E. J., and Smith, N. P.: Cardiac cell modelling: Obser- vations from the heart of the cardiac physiome project. In: Prog Biophys Mol Biol, 2010, in press. [9] Gonzalez, R. and Woods, R.: Digital image processing. Addison

a colloquium day starting with an overview of the history of COMBINE by Mike Hucka (California Institute of Technology, USA), one of the co-founders of COMBINE. Subsequently, Peter Hunter (University of Auckland, New Zealand) gave a keynote lecture in the HITS colloquium series. He showed recent developments in computational physiology with a focus on novel developments within the Physiome Project [ 19 ]. The Physiome Project is developing model and data encoding standards, web accessible databases and open source software for multiscale modeling ( http

—-Huxley equations applicable to purkinje fibre action and pacemaker potentials. The Journal of Physiology, ():–, . [] D. Noble, A. Garny, and P. J. Noble. How the Hodgkin-Huxley equations inspired the cardiac physiome project. The Journal of Physiology, (Pt ):–, . [] K. Rinke, F. Jost, R. Findeisen, T. Fischer, R. Bartsch, E. Schalk, and S. Sager. Parameter estimation for leukocyte dynamics after chemotherapy. In Proceedings of the Foundations of Systems Biolo- gy in Engineering (FOSBE) Conference, volume , pages –. Magdeburg, Germany