If is becoming clear that the emergent, integrative behaviors of biological
systems result from complex interactions between all system components, an
d that knowledge of each component is not sufficient to understand such beh
aviors. In this paper, we describe our approach to the integrative modeling
of cardiac function. This approach spans multiple levels of biological ana
lysis, ranging from subcellular to tissue. We have applied diverse analytic
al methods, including imaging techniques for measurement of anatomic struct
ure and biophysical and biochemical responses of cells and tissue, parallel
computing techniques for the numerical solution of large systems of model
equations, and interactive visual exploration of model dynamic behavior.