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  <title><![CDATA[Small Systems Biology]]></title>
  <body><![CDATA[<p><strong>TITLE:</strong> Small Systems Biology</p><p><strong>SPEAKER:</strong> Professor Eberhard O. Voit</p><p><strong>ABSTRACT:</strong></p><p>The combination of high-throughput methods of molecular biology with 
advanced mathematical and computational techniques has propelled the 
emergent field of systems biology into a position of prominence. 
Unthinkable only a decade ago, it has become possible to screen and 
analyze the expression of entire genomes, simultaneously assess large 
numbers of proteins and their prevalence, and characterize in detail the 
metabolic state of a cell population. While very important, the focus on 
comprehensive networks of biological components is only one side of 
systems biology. Complementing large-scale assessments, and sometimes at 
risk of being forgotten, are more subtle analyses that rationalize the 
design and functioning of biological modules in exquisite detail. This 
intricate side of systems biology aims at identifying the specific roles 
of processes and signals in smaller, fully regulated systems by 
computing what would happen if these signals were lacking or organized 
in a different fashion. I will exemplify this type of approach with two 
examples. The first is a detailed analysis of the regulation of glucose 
utilization in <em>/Lactococcus lactis/</em>. This organism is exposed to 
alternating periods of glucose availability and starvation. During 
starvation, it accumulates an intermediate of glycolysis, which allows 
it to take up glucose immediately upon availability. This notable 
accumulation poses a non-trivial control task that is solved with an 
unusual, yet ingeniously designed and timed feedforward activation 
system. The elucidation of this control system required high-precision 
<em>/in vivo/</em> data on the dynamics of intracellular metabolite pools, 
combined with methods of nonlinear systems analysis, and may serve as a 
paradigm for multidisciplinary approaches to fine-scaled systems 
biology. The second example describes our attempts to understand signal 
transduction in the human brain, along with perturbations in diseases 
like Parkinson’s disease and Schizophrenia.
<br />
<br />
<br />*/References:/*
<br />
<br />Voit, E.O.: /Computational Analysis of Biochemical Systems. A Practical 
Guide for Biochemists and Molecular Biologists/, xii + 530 pp., 
Cambridge University Press, Cambridge, U.K., 2000.
<br />
<br />Voit, E.O., A.R. Neves, and H. Santos. The Intricate Side of Systems 
Biology. <em>/PNAS/</em>, 103(25), 9452-9457, 2006.
<br />
<br />Qi, Z., G. W. Miller, and E. O. Voit: Computational analysis of 
determinants of dopamine dysfunction. <em>/Synapse/</em>* 63*: 1133-1142, 2009.
<br />
<br />Wu, Jialiang, Z. Qi, and E.O. Voit: Investigation of delays and noise in 
dopamine signaling with hybrid functional Petri nets. In Silico Biol. 
10, 0005 (2010).</p>]]></body>
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