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Successful physiological analysis requires an understanding of the functional interactions between the key components of cells, organs, and systems, as well as how these interactions change in disease states. This information resides neither in the genome nor even in the individual proteins that genes code for. It lies at the level of protein interactions within the context of subcellular, cellular, tissue, organ, and system structures. 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 the development of powerful computing hardware and algorithms have made it possible to explore functionality in a quantitative manner all the way from the level of genes to the physiological function of whole organs and regulatory systems. This review illustrates this development in the case of the heart. Systems physiology of the 21st century is set to become highly quantitative and, therefore, one of the most computer-intensive disciplines.

Original publication




Journal article



Publication Date





1678 - 1682


Animals, Arrhythmias, Cardiac, Computer Simulation, Coronary Circulation, Drug Evaluation, Preclinical, Genes, Genome, Heart, Heart Diseases, Humans, Markov Chains, Models, Cardiovascular, Myocardium, Proteins, Proteome