As reductionist experimental biology provides increasingly detailed information on the molecular components of biological systems and their alterations in disease states, the need grows for quantitative analyses that can integrate this information to predict and explain in-vivo phenotypes. Computation and information technology have become essential for integrating diverse biological data from genomics to clinical medicine. Data integration has been the emphasis of Bioinformatics. In-silico models can integrate functionally across the molecular components of biological networks or between interacting physiological sub-systems such as those responsible for energy metabolism, signal transduction, and ionic balances. This is the focus of Systems Biology. They can also integrate structurally across physical scales of biological organization from single molecule to whole organism. This is now often referred to as Multi-Scale Computational Biology.
We present the use of computational analysis for data, functional and structural integration in studying the electromechanics of the normal and diseased heart including recent studies of: (a) cell systems modeling of beta-adrenergic signaling and excitation-contraction coupling in acquired and genetic disease; and (b) multi-scale models of single myocytes, multicellular tissue preparations and whole heart electromechanics in normal and failing hearts.
Audio (MP3 File, Podcast Ready)
Copyright. All Rights Reserved.