مدل سازي مبتني بر شبكه ي پتري مسير زيستي كم اكسيژني ﴿هيپوكسي﴾

چكيده انگليسي :

Modeling of Hypoxia Pathway Using Petri Nets Zarifeh Heidary z heidary@ec iut ac ir Date of Submission Sep 13 2014 Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Supervisor Jafar Ghaisari ghaisari@cc iut ac ir Abstract Systems biology is a new research field that focuses on the understanding of biological processes based on the relation between engineering mathematics and biology In spite of complexity of these systems in comparison with industrial systems systems biology facilitated the use of control theory in the study of biological phenomena Thus control engineering tools such as system identification modeling design and analysis may solve some problems in systems biology In order to identify the dynamics of a system and predict its behavior in the absence of the experimental data modeling can be used The model of a biological phenomenon is actually a simplified map of its behavioral mechanisms and in addition to identifying the system it can be used in investigation of biological hypotheses which have not still been tested experimentally Mathematical modeling of biological systems can be classified in two categories quantitative and qualitative Quantitative modeling requires precise and detailed information from biological processes which usually are not available so it has led us to the use of qualitative modeling Among qualitative methods Petri nets are an appropriate graphical modeling tool which may serve in modeling complex biological interactions Also by using high level petri nets such as colored timed hybrid and stochastic petri nets quantitative information can be used in modeling process thus a comprehensive model of the biological process is created One of the biological processes which may occur due to the various reasons in living organisms is the activation of hypoxia pathway Hypoxia is a condition in which oxygen supply to living tissues is reduced and the persistence of this situation may lead to heart artery disease stroke kidney disease cancer and obstructive lung diseases Therefore identification and modeling of cellular processes in response to hypoxic condition is important In this thesis identifying and modeling of hypoxia pathway are done by the use of stochastic Petri nets and with the comparison between modeling results and experimental data it is observed that the model describes the biological process behavior truly Sensitivity analysis is also performed on the model and key reactions in biological pathway are specified Then by analyzing the results obtained from the model cellular control mechanisms in expression of several important proteins which are involved in this pathway and the hypothesis for existence of a possible drug for controlling the effective processes in response to hypoxic condition are introduced Quantitative model are a modeling method in order to parameter estimation and other mathematical analysis of biological systems Also a quantitative model based on differential equations governing the hypoxia pathway is presented and the results are compared with experimental data and qualitative model results Keywords Hypoxia pathway Modeling Stochastic Petri nets Systems biologyPDF created with pdfFactory Pro trial version www pdffactory com

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مدل سازي مبتني بر شبكه ي پتري مسير زيستي كم اكسيژني ﴿هيپوكسي﴾

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