Biology and physics competencies for pre-health and other life sciences students.

The recent report on the Scientific Foundations for Future Physicians (SFFP) and the revised Medical College Admissions Test (MCAT) reframe the preparation for medical school (and other health professional schools) in terms of competencies: what students should know and be able to do with that knowledge, with a strong emphasis on scientific inquiry and research skills. In this article, we will describe the thinking that went into the SFFP report and what it says about scientific and quantitative reasoning, focusing on biology and physics and the overlap between those fields. We then discuss how the SFFP report set the stage for the discussion of the recommendations for the revised MCAT, which will be implemented in 2015, again focusing the discussion on biology and physics.

The transition between stochastic and deterministic behavior in an excitable gene circuit.

We explore the connection between a stochastic simulation model and an ordinary differential equations (ODEs) model of the dynamics of an excitable gene circuit that exhibits noise-induced oscillations. Near a bifurcation point in the ODE model, the stochastic simulation model yields behavior dramatically different from that predicted by the ODE model. We analyze how that behavior depends on the gene copy number and find very slow convergence to the large number limit near the bifurcation point.

Stochastic coherence in an oscillatory gene circuit model.

We show that noise-induced oscillations in a gene circuit model display stochastic coherence, that is, a maximum in the regularity of the oscillations as a function of noise amplitude. The effect is manifest as a system-size effect in a purely stochastic molecular reaction description of the circuit dynamics. We compare the molecular reaction model behavior with that predicted by a rate equation version of the same system.

Fokker-Planck analysis of stochastic coherence in models of an excitable neuron with noise in both fast and slow dynamics.

We provide a detailed and quantitative Fokker-Planck analysis of noise-induced periodicity (stochastic coherence, also known as coherence resonance) in both a discrete-time model and a continuous-time model of excitable neurons. In particular, we show that one-dimensional models can explain why the effects of noise added to the fast and slow dynamics of the models are dramatically different. We argue that such effects should occur in any excitable system with two or more distinct time scales and need to be taken into account in experiments investigating stochastic coherence.