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<strong></strong><h3><em>Review Article</em></h3> <p><strong>Computational biology of cardiac myocytes: proposed standards for the physiome</strong></p> <p><strong>Nicolas P. Smit, Edmund J. Crampin, Steven A. Niederer, James B. Bassingthwaighte and Daniel A. Beard<sup>.</sup></strong></p> <p><em>University Computing Laboratory, University of Oxford, Oxford, OX1 3QD, UK, Bioengineering Institute, University of Auckland, Auckland, New Zealand, University of Washington, Seattle, USA, Medical College Wisconsin, WI, USA</em> </p> <p><strong>Summary </strong></p> <p>Predicting information about human physiology and pathophysiology from genomic data is a compelling, but unfulfilled goal of post-genomic<sup> biology</sup>. This is the aim of the so-called Physiome Project and is, undeniably, an ambitious goal. Yet if we can exploit even a small proportion of the rich and varied experimental data currently available, significant insights into clinically important aspects of human physiology will follow. To achieve this requires the integration of data from disparate sources into a common framework. Extrapolation of available data across species, laboratory techniques and conditions requires a quantitative approach. Mathematical models allow us to integrate molecular information into cellular, tissue and organ-level, and ultimately clinically relevant scales. In this paper we argue that biophysically detailed computational modelling provides the essential tool for this process and, furthermore, that an appropriate framework for annotating, databasing and critiquing these models will be essential for the development of integrative computational biology. </p> <p>Key words: physiome, mathematical modelling, cardiac, multi-scale.</p> <p><em>Journal of Experimental Biology 210, 1576-1583 (2007). Published by The Company of Biologists 2007. <br></em></p>
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