TY - GEN
T1 - Mining for variability in the coagulation pathway
T2 - 11th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2013
AU - Castaldi, Davide
AU - Maccagnola, Daniele
AU - Mari, Daniela
AU - Archetti, Francesco
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
KW - Coagulation
KW - Petri Nets
KW - Stochastic Simulation
KW - Systems Biology
KW - Variability Analysis
UR - http://www.scopus.com/inward/record.url?scp=84875088912&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84875088912&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-37189-9_14
DO - 10.1007/978-3-642-37189-9_14
M3 - Conference contribution
AN - SCOPUS:84875088912
SN - 9783642371882
VL - 7833 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 153
EP - 164
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Y2 - 3 April 2013 through 5 April 2013
ER -