[Bionews] MSBF Colloquium, Thu June 16, Frank J. Doyle: A "Systems" Approach to Modeling and Analyzing Biological Systems

Johannes W. Dietrich j.w.dietrich.mt at medizinische-kybernetik.de
Mon Jun 6 06:50:44 EST 2005


X-Delivery-Time: 1118058005
Date: Mon, 6 Jun 2005 13:36:03 +0200
From: Christoph Best <best at biochem.mpg.de>
Subject: [msbf-announce] MSBF Colloquium, Thu June 16, Frank J. Doyle: A 
"Systems" Approach to Modeling and Analyzing Biological Systems
To: MSBF Announcements Mailing List <announce at sysbio-muenchen.de>



                        M S B F    C O L L O Q U I U M
 
                             Frank J. Doyle III

                Department of Chemical Engineering and 
              Institute for Collaborative Biotechnologies,
             University of California, Santa Barbara, Calif.


      A "Systems" Approach to Modeling and Analyzing Biological Systems


                  17:00 - 18:30, Thursday, June 16, 2005
                  Kleiner Hörsaal II, Biozentrum der LMU,
                    Großhaderner Str. 2, Martinsried

            http://www.sysbio-muenchen.de/msbf-colloquium.html

   Abstract:

   Understanding regulation is a critical hurdle in unraveling complex
   biological systems. As gene-level architectures become known, the open
   challenge is to assign predictable behavior to a known structure, the
   so-called genotype-to-phenotype problem.

   In response to this challenge, the discipline of systems biology has
   emerged with an integrative perspective towards determining complex
   systems behavior. A property of particular interest is the /robustness
   /of the biophysical network: the ability to maintain some target level
   of behavior or performance in the presence of uncertainty and/or
   perturbations. In biological systems, these disturbances can be
   environmental (heat, pH, etc.) or intrinsic to the organism (changes
   in kinetic parameters). While preliminary results are available for
   simple (low-dimensional, deterministic) biological systems, general
   tools for analyzing these tradeoffs are the subject of active
   research.

   The gene network which underlies circadian rhythms is an ideal system
   for robustness studies, owing to its remarkable performance in a
   highly uncertain environment. Of interest for control theoretic
   analyses, the dominant elements of the postulated architecture for
   Drosophila consist of nested negative autoregulatory feedback loops
   controlling the expression of timeless (tim) and period (per)
   interlocked with a positive feedback loop established via the dClock
   gene. Complex formation, regulated translocation and degradation of
   several of these gene products, which is additionally controlled (and
   delayed) by protein phosphorylation, add further levels of complexity
   to the system.

   In this talk, a number of quantitative tools from systems theory will
   be presented as enabling methodologies for unraveling robust
   biological regulatory systems, with an emphasis on sensitivity
   analysis. Our work on modeling and analysis of the Drosophila
   circadian rhythm gene network will be detailed, and generalizations
   will be drawn for the mammalian analog and for more general gene
   regulatory networks.


   How to get to the Biozentrum:

   Take U6 to the "Großhadern" stop (one before the final stop
   "Klinikum"), and take the Bus 266 "Planegg" for three stops/four 
minutes
   to "Großhaderner Straße". Total travel time from LMU main campus is
   about 30 minutes.

-- 
| Christoph Best      <best at biochem.mpg.de>       
http://www.rzg.mpg.de/~cbest
| Max-Planck-Institute of Biochemistry, Munich, Germany       
+49-89-8578 2634




Attachments
-----------
  msbf-seminar-10.pdf  
<http://www.sysbio-muenchen.de/msbf-announce/47_1.pdf>

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-- 

-- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --
-- Dr. Johannes W. Dietrich, Medical Cybernetics
-- Sektion Endokrinologie, Universitaetsklinikum Ulm
-- Robert-Koch-Str. 8, D-89081 Ulm, Germany
-- Phone: +49:731:500-24301, Fax: +49:731:500-24302
-- WWW: http://medical-cybernetics.de
-- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --




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