<!doctype html public "-//W3C//DTD W3 HTML//EN">
<html><head><style type="text/css"><!--
blockquote, dl, ul, ol, li { padding-top: 0 ; padding-bottom: 0 }
--></style><title>MOS April 5, 2005</title></head><body>
<div><font face="Arial" size="+2" color="#000000">Seminar
on</font></div>
<div><font face="Arial" size="+2" color="#000000"><b>Modern Optics and
Spectroscopy</b></font></div>
<div><font face="Arial" size="+2"
color="#000000"><b><br></b></font></div>
<div><font face="Arial" size="+2" color="#000000"><b>Alexander van
Oudenaarden</b>, MIT</font></div>
<div><font face="Arial" size="+2" color="#000000"><br></font></div>
<div><font face="Arial" size="+2" color="#000000"><i><b>How does a
single cell remember</b></i></font></div>
<div><font face="Arial" size="+2" color="#000000"><i><b><br>
</b></i>April 5, 2005</font></div>
<div><font face="Arial" size="+2" color="#000000">12:00 - 1:00
p.m.</font></div>
<div><font face="Arial" size="+2" color="#000000">Grier Room
34-401<br>
<br>
<br>
Abstract<br>
</font></div>
<div><font face="Arial" size="+2">Upon induction of cell
differentiation, distinct cell phenotypes are encoded by complex
genetic networks. These networks can prevent the reversion of
established phenotypes even in the presence of significant
fluctuations. In this talk I will explore the key parameters that
determine the stability of cellular memory using gene networks in the
bacterium<i> Escherichia coli</i> and the budding yeast<i>
Saccharomyces cerevisiae</i> as model systems. These networks contains
multiple nested feedback loops responsible for storing the cellular
memory. The parameters that determine the stability of the cellular
memory are identified by systematically opening the underlying
feedback loops. These experiments are complemented by stochastic and
stability analyses. These observations provide quantitative
understanding of stability and reversibility of cellular
differentiation states.</font></div>
</body>
</html>