**THE MALLAT FAMILY FUND FOR RESEARCH IN
MATHEMATICS **

**invites**** you to a**

**DISTINGUISHED LECTURE
SERIES****
**

**to**** be
presented by**

Duke

The lectures will be
held in

Room
001

Technion - Israel Institute of Technology

Lecture
I:

Room
001,

**Probability and Neurobiology**

Neurons are
inherently variable devices and therefore an important general question in the
study of the central nervous system is how we can make accurate calculations
with (large numbers of) imperfect devices. This question is particularly
pertinent in the auditory system where behavioral studies show that mammals can
detect extremely small time differences. After a brief introduction to the
auditory system, experimental data will be presented that show that the
question is serious indeed. A natural abstraction of the question leads to a
(not so simple) problem in probability theory for which analytical and
computational results (with Colleen Mitchell) will be presented. Recent
theoretical results suggest that the behavior of some real neurons is similar
to the behavior of the abstract neurons. Experiments are currently underway to
see if this is true.

Lecture
II:

Room
001,

**Cell Metabolism, Mathematics, and Public Health**

Folate and methionine metabolism, a small part of
cell biochemistry, is crucial for cell replication and DNA methylation.
There is mounting evidence that the mechanisms by which some gene polymorphisms
or dietary deficiencies are statistically linked to heart disease and certain
cancers involve disruptions of folate and methionine metabolism. Folate
metabolism is also the target of several chemotheraputic
agents and some antibiotics target folate metabolism
in bacteria. A collaborative mathematical modeling project (with Cornelia
Ulrich of the Fred

Lecture
III:

Room
001,

**Propagation of Fluctuations Through
Bio-chemical Networks**

Analysis of
the propagation of stochastic fluctuations through bio-chemical networks poses
new, interesting mathematical problems and has proven to be a useful tool for
understanding biological function. For each signal, either external or
internal, that causes a particular cell to
dramatically change its operation, there are two natural questions. First, how
does the gene-biochemical network respond to accomplish the change? Second, how
does the network enable the cell to maintain homeostasis in all its other
operations despite the change? One would like to understand the structural and
kinetic principles that allow the network to accomplish both tasks
simultaneously. Two distinct approaches will be described. First, we study how
fluctuations propagate through relatively simple systems. We are interested in
discovering how different network geometries magnify or suppress fluctuations since this may give clues to why biochemical networks
look the way they do. Secondly, we apply fluctuations to in silico
representations of specific biological networks. By observing how fluctuations
propagate we can identify reactions or subsystems that are buffered against
such fluctuations, i.e. are homeostatic. Then, through in silico
experimentation (e.g. removing particular reactions), we can take the system
apart piece by piece to discover the regulatory mechanisms that give rise to
the homeostasis