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 at 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 at 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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