System Level Mathematical Analysis of Mitosis
- Date: 09/06/2006
Alex Mogilner (University of California, Davis)
University of British Columbia
Mitotic spindle goes through distinct morphological states
characterized by increasing spindle length and distances between
chromosomes. A complete picture of how the spindle assembles is still
lacking. We performed an In Silico model screen to identify all
potential mechanisms of spindle self-organization. We trained' the
computer to assemble a set of models and screened the models in a
multi-dimensional parameter space. To identify models that fit
experimental data we used stochastic optimization and genetic
algorithms. We found multiple models quantitatively describing the
spindle in which the timing of force activity must be fine tuned, in
contrast to the kinetic and mechanical parameters that show robustness
to change.
Alex Mogilner graduated in 1985 with an M.Eng. in Engineering Physics
from the Ural Polytechnic Institute in Sverdlovsk (then USSR), followed
by a Ph.D. in Physics from the USSR Academy of Sciences in 1990. He
then obtained his second Ph.D. in Applied Mathematics at the University
of British Columbia in 1995. His main fields of expertise are
mathematical biology and cell and molecular biophysics. Specifically,
he investigates biological movements on the molecular, cellular, and
multicellular levels.
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