Tyler Earnest, John Cole, and Zaida Luthey-Schulten.
Simulating biological processes: Stochastic physics from whole cells
to colonies.
Reports on Progress in Physics, 81:052601, 2018.
EARN2018-ZLS
The last few decades have revealed the living cell to be a crowded spatially
heterogeneous space teeming with biomolecules whose concentrations
and activities are
governed by intrinsically random forces. It is from this randomness,
however, that a
vast array of precisely timed and intricately coordinated biological
functions emerge
that give rise to the complex forms and behaviors we see in the biosphere
around
us. This seemingly paradoxical nature of life has drawn the interest of an
increasing
number of physicists, and recent years have seen stochastic modeling
grow into a major
subdiscipline within biological physics. Here we review some of the major
advances
that have shaped our understanding of stochasticity in biology. We begin
with some
historical context, outlining a string of important experimental results that
motivated
the development of stochastic modeling. We then embark upon a fairly
rigorous
treatment of the simulation methods that are currently available for the
treatment
of stochastic biological models, with an eye toward comparing and
contrasting their
realms of applicability, and the care that must be taken when
parameterizing them.
Following that, we describe how stochasticity impacts several key
biological functions,
including transcription, translation, ribosome biogenesis, chromosome
replication, and
metabolism, before considering how the functions may be coupled into a
comprehensive
model of a “minimal cell.” Finally, we close with our expectation for the
future of the
field, focusing on how mesoscopic stochastic methods may be augmented
with atomic-
scale molecular modeling approaches in order to understand life across a
range of length
and time scales.
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