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The successful analysis of physiological processes requires quantitative understanding of the functional interactions between the key components of cells, organs and systems, and how these interactions change in disease states. This information does not reside in the genome, or even in the individual proteins that genes code for. There is therefore no alternative to copying nature and computing these interactions to determine the logic of healthy and diseased states. The rapid growth in biological databases, models of cells, tissues and organs, and in computing power has made it possible to explore functionality all the way from the level of genes to whole organs and systems. Examples are given of genetic modifications of the Na+ channel protein in the heart that predispose people to ventricular fibrillation, and of multiple target therapy in drug development. Complexity in biological systems also arises from tissue and organ geometry. This is illustrated using modelling of the whole heart.


Journal article


Novartis Found Symp

Publication Date





111 - 123


Animals, Anti-Arrhythmia Agents, Biochemical Phenomena, Biochemistry, Computer Simulation, Gene Expression, Genome, Heart Failure, Humans, Models, Biological, Mutation, Nonlinear Dynamics, Physiology, Proteins, Proteome