| Simulating FAS-induced apoptosis by using P systems |
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| 作者姓名： | Smitha Cheruku Andrei P?un Francisco J. Romero-Campero Mario J. Pérez-Jiménez and Oscar H. Ibarra |
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| 作者单位： | 1. Department of Computer Science/IfM, Louisiana Tech University, P.O. Box 10348, Ruston, LA 71272, USA; 2. Department of Computer Science and Artificial Intelligence, University of Seville, Avda. Reina Mercedes s/n 41012, Sevilla, Spain； 3. Department of Computer Science, University of California -Santa Barbara, Santa Barbara, CA 93106, USA |
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| 基金项目： | A. Paun gratefully acknowledges the support in part by LA BoR RSC grant LEQSF (2004-07)-RD-A-23 and NSF Grants IMR-0414903 and CCF-0523572，O. H. Ibarra gratefully acknowledges the support in part by NSF Grants CCR-0208595, CCF-0430945 and CCF-0524136 |
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| 摘 要： | In contrast to differential equations, P systems are an unconventional model of computation which takes into consideration the discrete character of the quantity of components and the inherent randomness that exists in biological phenomena. The key feature of P systems is their compartmentalised structure which represents the heterogeneity of the structural organisation of the cells, and where one can take into account the role played by membranes in the functioning of the system, for example signalling at the cell surface, selective uptake of substances from the media, diffusion across different compartments, etc. We show here that P systems can be a reliable tool for Systems Biology and could even outperform in some cases the current simulation techniques based on differential equations. We will also use a strategy based on the well known Gillespie algorithm but running on more than one compartment called Multi-compartmental Gillespie Algorithm.
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Simulating FAS-induced apoptosis by using P systems |
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| Authors: | Smitha Cheruku Andrei Paun Francisco J Romero-Campero Mario J Perez-Jimenez and Oscar H Ibarra |
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| Abstract: | In contrast to differential equations, P systems are an unconventional model of computation which takes into consideration the discrete character of the quantity of components and the inherent randomness that exists in biological phenomena. The key feature of P systems is their compartmentalised structure which represents the heterogeneity of the structural organisation of the cells, and where one can take into account the role played by membranes in the functioning of the system, for example signalling at the cell surface, selective uptake of substances from the media, diffusion across different compartments, etc. We show here that P systems can be a reliable tool for Systems Biology and could even outperform in some cases the current simulation techniques based on differential equations. We will also use a strategy based on the well known Gillespie algorithm but running on more than one compartment called Multi-compartmental Gillespie Algorithm. |
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| Keywords: | FAS-induced apoptosis P systems deterministic waiting times algorithm multi-compartmental Gillespie algorithm |
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