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From: Animesh_Ray@kgi.edu (Animesh Ray)
Subject: Postdoctoral Associate Position available
Date: 27 Oct 2001 00:54:22 +0100
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My laboratory at the Keck Graduate Institute
(www.kgi.edu) is seeking
creative and independent postdoctoral researchers
 preferably with training
 in yeast molecular genetics and with interest in
 analysis of complex gene
 regulatory networks.  The individual will lead
 experimental analysis of gene
 regulatory network by whole-genome mRNA expression
 profiling in wild type
 and mutant yeast strains.  Candidates with prior
 experience in mRNA
 micro-array analysis will have an advantage.  There
 will be opportunity for
 close interaction with a team of computational
 biologists.  The NSF Program
 in Quantum and Biological Computing funds this
 interdisciplinary project,
 which aims to explore the basis of robustness in
 gene regulatory networks
 and apply the findings to the design of human
 communication network.
 (Please see below a project summary)
  
 KGI is located 35 miles east of Los Angeles, at the
 foot of the San Gabriel
 Mountains. Its campus is contiguous with those of
 the other Claremont
 Colleges, which together with surrounding
educational institutions in
 Southern California provide a rich intellectual and
 cultural environment.
 KGI is dedicated to innovative research and teaching
 at the forefront of
 applied biology, and its faculty, students, and
 associates have strong ties
 with the biotechnology industry.
 
 Prospective candidates should apply with a cover
 letter stating areas of
 research interest, enclose a CV, and ask for three
 letters of recommendation
 to be sent to me at: Keck Graduate Institute, 535
 Watson Drive, Claremont,
 CA 91711.  Email: Animesh_Ray@kgi.edu 
 
 Animesh Ray
 Associate Professor
 Keck Graduate Institute
 535 Watson Drive
 Claremont, CA 91711
 phone: (909) 607-9729
 fax: (909) 607-8086
 e-mail: animesh_ray@kgi.edu
 Associate Professor Adjunct
 Division of Biology
 University of California San Diego
 &
 Visiting Associate Professor
 University of Rochester
 Rochester, NY
 
 Causes of Robustness and Vulnerability in Real-World
 Networks: Lessons From
 Molecular Biology
 
 
 PI: Animesh Ray
 Co-PI: David Galas, Gregory Dewey, Amarnath Gupta,
 Mitsunori Ogihara
  
 Summary
 
 Vulnerability of natural networks (such as the
 Internet, power supply grid,
 or molecular regulatory circuits of cells) to
 accidental or deliberate
 attack is an important area of study.  Results from
 such studies provide
 guidelines for designing robust communication
 infrastructure that are more
 resistant to disruption.  To date most work has
 focused on observations of
 existing static networks or on computer simulations,
 because most natural
 networks are difficult to manipulate experimentally.
 Prior work has revealed
 certain fundamental global properties common to all
 natural networks.  This
 raises the possibility that the study of one
 representative natural network
 by direct experimental manipulation could illuminate
 general properties of
 most networks.  Complex molecular machinery
 regulating the synthesis of RNA
 molecules in the nucleus of budding yeast, a
 single-celled organism, is a
 real-world instance of a natural network that can be
 experimentally
 perturbed by defined genetic manipulations, and the
 results of these
 perturbations can be studied at the molecular level
 with unprecedented
 accuracy by current genomic techniques.  We propose
 to use this biological
 system to study the properties of a natural network
 as a function of precise
 disruptions, which will enable refinement of
 conceptual models by direct
 experiments.  Systematic gene knockout mutations
 (equivalent to node
 removal), regulatory site deletion mutations
 (equivalent to edge removal),
 and artificially directed gene activation
 (equivalent to edge addition) will
 be used as tools to actively alter a network. 
 Effects of this rich variety
 of perturbations in the gene regulatory network
 architecture will be
 analyzed at the level of whole-genome
 transcriptional profiles. Analysis of
 these transcriptional patterns will be complemented
 by queriable
 database-dependent computer simulation, and through
 existing knowledge base
 in yeast genetics.  This interplay will allow basic
 properties of robustness
 and vulnerability of this complex natural network to
 be inferred through
 detailed hypothesis testing.  Design principles
 underlying the architecture
 of these evolutionarily successful complex networks
 will be probed.
 Insights obtained from these studies will be
 valuable for defensive
 strategies in complex network design, with
 implications in, among others,
 communication technology, disaster response, and in
 designing robust
 communication infrastructure resistant to planned
 attacks.  
 
 
 
 
 ---
  

=====



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bionet.genome.gene-structure



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