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Modeling Integrated Cellular Machinery Using Hybrid Petri-Boolean Networks
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@MISC{Berestovsky_modelingintegrated,
author = {Natalie Berestovsky and Ing Zhou and Deepak Nagrath and Luay Nakhleh},
title = {Modeling Integrated Cellular Machinery Using Hybrid Petri-Boolean Networks},
year = {}
}
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Abstract
The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM) that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and
Keyphrases
good agreement integrated network biological function different time scale cellular osmoregulation major biological process petri net phenotypic change transcriptional regulation integrated cellular machinery integrated hybrid model transcription regulation human cell stochastic simulation mechanism boolean network computational complexity biochemical reaction entire system signal transduction certain cellular phenomenon produce signal computational technique testable hypothesis cellular circuitry experimental data integrated cellular network glucose metabolism
