MINING FOR VARIABILITY IN THE COAGULATION PATHWAY: A SYSTEMS BIOLOGY APPROACH
| Autor: | Francesco Archetti, Daniela Mari, Davide Castaldi, Daniele Maccagnola |
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| Přispěvatelé: | Castaldi, D, Maccagnola, D, Mari, D, Archetti, F |
| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: | |
| Zdroj: | Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics ISBN: 9783642371882 EvoBIO |
| Popis: | In this paper authors perform a variability analysis of a Stochastic Petri Net (SPN) model of the Tissue Factor induced coagulation cascade, one of the most complex biochemical networks. This pathway has been widely analyzed in literature mostly with ordinary differential equations, outlining the general behaviour but without pointing out the intrinsic variability of the system. The SPN formalism can introduce uncertainty to capture this variability and, through computer simulation allows to generate analyzable time series, over a broad range of conditions, to characterize the trend of the main system molecules. We provide a useful tool for the development and management of several observational studies, potentially customizable for each patient. The SPN has been simulated using Tau-Leaping Stochastic Simulation Algorithm, and in order to simulate a large number of models, to test different scenarios, we perform them using High Performance Computing. We analyze different settings for model representing the cases of "healthy" and different " unhealthy" subjects, comparing and testing their variability in order to gain valuable biological insights. © 2013 Springer-Verlag. |
| Databáze: | OpenAIRE |
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