مدل سازي مبتني بر شبكه هاي پتري مسير انتقال سيگنال TGF- Bدر سلول

چكيده انگليسي :

78 A Petri Net Modeling and Analysis of TGF Pathway in Cell Niloofar Nickaeen n nickaeen@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 Mathematical modeling and analysis of biological systems leads to attain further knowledge inbiological fields and thus pave the way for prevention and treatment of diseases Particularly in the last twodecades engineering and applied mathematics has been widely used in modeling and analysis of biologicalnetworks Among various techniques for modeling and analyzing biological systems Petri nets due to theircomputational and graphical capabilities have attracted much attention Flexibility and simplicity of thesenets along with their ability to model simultaneous reactions has made these nets the suitable tool formodeling biological systems Signal transduction pathways are sets of processes that enable the cell tocommunicate with its various departments and also adjacent cells One of the signal transduction pathwaysof a cell is the TGF pathway Any interruption in this signal transduction path may be followed by celldestruction In this thesis a stochastic Petri net model of the signal transduction pathway based on scientificknowledge and experimental data is proposed The main purpose of modeling the transduction system is tosearch the response range of the system to investigate the ability of the system to produce experimental dataobtained from in vivo experiments In spite of the ability of the Petri model to justify and reproduce theexperimental data it seems another modeling tool with more computational capabilities might be needed For example to perform sensitivity or centrality analysis Petri nets do not offer proper computational tools Differential equations on the other hand are an appropriate choice in this matter as they provide morecomputational and analysis options For example to perform sensitivity analysis differential equationsprovide straight forward computational options compared to Petri nets So a system of differentialequations is presented to describe the signal transduction pathway By comparing Petri model and thesystem of differential equations representing the TGF pathway and also their output responses withexperimental data advantages and disadvantages of each modeling method is investigated and compared Although Petri nets do not enjoy the vast computational capabilities of differential equations their ability tomodel qualitative and quantitative features of the system in one model makes them more appropriate formodeling biological systems in which many aspects are qualitatively known In the discussed signal transduction pathway increment of certain proteins in the cell leads to celldestruction Experimental results also confirm the incident Next a standard Petri net based controller isproposed to control the increment of these proteins thus cell growth The results are translated to the form ofstoichiometric equations for the usage of biologists Keywords TGF signaling pathway Stochastic Petri nets Modeling biological pathway Control P invariants System biology Cell

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مدل سازي مبتني بر شبكه هاي پتري مسير انتقال سيگنال TGF- Bدر سلول

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