"A physicist's perspective on the complexity of biology"
Abstract: The complexity of biological systems arises from highly nonlinear structural, metabolic, and signaling networks that span multiple spatiotemporal scales. Massively parallel systems-biology experiments provide ever more dynamic data. As we acquire complete, reductionist parts list for simple biological systems, we must ascertain how these pieces interact--a mathematical model of a functioning animal might require Avogadro's number of partial differential equations, termed a Leibnitz. We are developing an integrated measurement and modeling system in which a computer specifies an experiment on organs-on-chips, the dynamic responses of the cells to a controlled stimulus are recorded using multiple real-time analytical techniques, and the computer then uses these data to select among possible models of the system and propose the next experiment for further model refinement. Preliminary results are encouraging--we only need to expand the approach by 23 orders of magnitude.