**3:45 - 4:15** :
Wei, Guowei
(Mathematics, Michigan State University)

-Title: **Differential geometry based multiscale models for
biomolecular systems**

-Abstract:

This talk focuses on a new multiscale paradigm developed at MSU
--- the differential geometry based multiscale models of
biomolecules. Under the physiological condition, most biological
processes, such as signal transduction, ion channel transport and
protein folding, occur in water, which consists of 65-90 percent
human cell weight. Therefore, solvent and synergy of solvent-solute
are important to the understanding of biomolecular structure,
function, dynamics and transport. I will discuss the use of differential
geometry theory of surfaces for coupling microscopic and macroscopic
scales at an equal footing. The biomolcule of interest is described
by discrete atomic and quantum mechanical variables. While the aquatic
invironment is described by continuum hydrodynamical variables. We
derive the coupled geometric flow equation, Navier-Stokes equation,
and generalized Poisson-Boltzmann equation (PBE) to describe the dynamics
of the biomolecular systems. Applications will be discussed to protein
folding, ion channels, micro/nanofluidics, and nano-bio sensors.

Acknowledgment:
This work was supported by NSF and NIH grants.

**4:15 - 4:45** :
Yamada, Richard
(Mathematics, University of Michigan-Ann Arbor)

-Title: ** Molecular Noise Enhances Oscillations in the Supra-Chiasmatic
Nuclei Network**

-Abstract:
In this talk, we will discuss a detailed mathematical model
for circadian timekeeping within the SCN. Our proposed model consists
of a large population of SCN neurons, with each neuron containing a
network of biochemical reactions involving the core circadian
components. Using mathematical modeling, our results show that both
intracellular molecular noise and intercellular coupling (nonlinear
in nature) are required to sustain stochastic oscillations in the SCN
oscillator network. Our work focuses on the problem of overcoming
noise in oscillator systems, and our results highlight the importance
of transcriptional noise in enhancing oscillations rather than
dampening them. Surprisingly, our predictions from our model have
been confirmed experimentally; we conclude with a short discussion of
these results.