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Cell-Cycle Genetic Control Modeling by Probabilistic Genetic Networks

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Author(s):
Nestor Walter Trepode
Total Authors: 1
Document type: Doctoral Thesis
Press: São Paulo.
Institution: Universidade de São Paulo (USP). Instituto de Matemática e Estatística (IME/SBI)
Defense date:
Examining board members:
Junior Barrera; Helena Paula Brentani; Marcelo Ribeiro da Silva Briones; Roberto Marcondes Cesar Junior; Carla Columbano de Oliveira
Advisor: Junior Barrera; Hugo Aguirre Armelin
Abstract

The cell division cycle comprises a sequence of phenomena controlled by a stable and robust genetic network. We applied a Probabilistic Genetic Network (PGN) to construct an hypothetical model with dynamical behaviour and robustness typical of the biological cell-cycle. The structure of our PGN model was inspired in well established biological facts such as the existence of integrator subsystems, negative and positive feedback loops and redundant signaling pathways. Our model represents genes\' interactions as stochastic processes and presents strong robustness in the presence of moderate noise and parameters fluctuations. A recently published deterministic yeast cell-cycle model collapses upon noise conditions that our PGN model supports well. In addition, self stimulatory mechanisms can give our PGN model the possibility of having a pacemaker activity similar to the observed in the oscillatory embryonic cell cycle. Our approach of modeling and simulating the observed behavior by known biological control mechanisms provides plausible hypotheses of how the underlying regulation may be performed in the cell. The ongoing research is lead to identify such regulation mechanisms in the yeast cell-cycle from time-series microarray gene expression data. (AU)