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Dr. Ilias Tagkopoulos
Department of Electrical Engineering
Princeton University
For more information please contact Dr. George Biros; gbiros@cc.gatech.edu
"Emergence of predictive internal representations in evolving biochemical networks"
Abstract:
The general principles governing the structure, function and evolution of regulatory networks have become dominant themes in systems biology: How do complex networks evolve through mutation and natural selection and how do environmental parameters (mutation rate, selection pressure, etc) affect their evolution?
To address these and other similar questions, I created a simulation framework (EVE – Evolution in Variable Environments) resembling a virtual ecology of microbial populations that compete, mutate and evolve in complex dynamic environments. I will discuss the various findings regarding the properties and evolutionary trajectory of these networks and I will show evidence that organisms, evolving randomly under precisely defined complex habitats, have the ability to capture the dynamical, multi-dimensional structure of diverse environments by internalizing the structured correlations of various environmental variables (e.g. temperature, oxygen, osmolarity, etc.). These results put into question the adequacy of homeostasis in explaining microbial behaviors and provide evidence that intracellular networks may achieve sophisticated modeling of habitat structure in a fashion similar to metazoan nervous systems. Finally, I will present physiological evidence that these computational results are relevant to bacterial behavior in nature and I will discuss novel findings regarding the interplay of network characteristics under various evolutionary pressures.
Bio:
Ilias Tagkopoulos has earned his PhD from the department of Electrical Engineering at Princeton University and he is currently affiliated with Princeton’s Lewis-Sigler Institute for Integrative Genomics and Credit Suisse's global derivatives group. His interests span a variety of topics related to engineering, finance and biology, ranging from software/hardware simulations of biological systems to biotechnology public policy and risk assessment of genetically modified organisms. He is a Burroughs Wellcome and PEI-STEP fellow.
http://www.princeton.edu/~iliast/aboutme.html
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