Mining for variability in the coagulation pathway: A systems biology approach

Davide Castaldi, Daniele Maccagnola, Daniela Mari, Francesco Archetti

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages153-164
Number of pages12
Volume7833 LNCS
DOIs
Publication statusPublished - 2013
Event11th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2013 - Vienna, Austria
Duration: Apr 3 2013Apr 5 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7833 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other11th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2013
CountryAustria
CityVienna
Period4/3/134/5/13

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Keywords

  • Coagulation
  • Petri Nets
  • Stochastic Simulation
  • Systems Biology
  • Variability Analysis

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Castaldi, D., Maccagnola, D., Mari, D., & Archetti, F. (2013). Mining for variability in the coagulation pathway: A systems biology approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7833 LNCS, pp. 153-164). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7833 LNCS). https://doi.org/10.1007/978-3-642-37189-9_14