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Tytuł artykułu

Preprocessing for Network Reconstruction : Feasibility Test and Handling Infeasibility

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The context of this work is the reconstruction of Petri net models for biological systems from experimental data. Such methods aim at generating all network alternatives fitting the given data. For a successful reconstruction, the data need to satisfy two properties: reproducibility and monotonicity. In this paper, we focus on a necessary preprocessing step for a recent reconstruction approach. We test the data for reproducibility, provide a feasibility test to detect cases where the reconstruction from the given data may fail, and provide a strategy to cope with the infeasible cases. After having performed the preprocessing step, it is guaranteed that the (given or modified) data are appropriate as input for the main reconstruction algorithm.
Wydawca
Rocznik
Strony
521--535
Opis fizyczny
Bibliogr. 15 poz., rys.
Twórcy
autor
  • Laboratoire d’Informatique, de Modélisation et d’Optimisation des Systèmes, Université Blaise Pascal (Clermont-Ferrand II), BP 10125, 63173 Aubière Cedex, France
  • Laboratoire d’Informatique, de Modélisation et d’Optimisation des Systèmes, Université Blaise Pascal (Clermont-Ferrand II), BP 10125, 63173 Aubière Cedex, France
Bibliografia
  • [1] M. Chen and W. Hofestädt. Quantitative Petri net model of gene regulated metabolic networks in the cell. In Silico Biology, 3:347–365, 2003.
  • [2] M. Durzinsky, W. Marwan, and A. K. Wagler. Reconstruction of extended Petri nets from time-series data by using logical control functions. Journal of Mathematical Biology, 66:203–223, 2013.
  • [3] M. Durzinsky, A. K. Wagler, and R. Weismantel. A combinatorial approach to reconstruct Petri nets from experimental data. In CMSB, volume 5307 of Lecture Notes in Computer Science, pages 328–346. Springer, 2008.
  • [4] M. Durzinsky, A. K.Wagler, and R.Weismantel. An algorithmic framework for network reconstruction. J. of Theor. Computer Science, 412(26):2800–2815, 2011.
  • [5] M. Favre and A. K. Wagler. Reconstructing X'-deterministic extended Petri nets from experimental timeseries data X'. In Preceedings of the 4th International Workshop on Biological Processes & Petri Nets, pages 45–59, 2013.
  • [6] I. Koch and M. Heiner. Petri nets. In B. H. Junker and F. Schreiber, editors, Biol. Network Analysis, Wiley Book Series on Bioinformatics, pages 139–179, 2007.
  • [7] W. Marwan, A. K.Wagler, and R.Weismantel. A mathematical approach to solve the network reconstruction problem. Math. Methods of Operations Research, 67(1):117–132, 2008.
  • [8] W. Marwan, A. K. Wagler, and R. Weismantel. Petri nets as a framework for the reconstruction and analysis of signal transduction pathways and regulatory networks. Natural Computing, 10:639–654, 2011.
  • [9] J. W. Pinney, R. D. Westhead, and G. A. McConkey. Petri net representations in systems biology. Biochem. Soc. Tarns., 31:1513–1515, 2003.
  • [10] C. Starostzik and W. Marwan. Functional mapping of the branched signal transduction pathway that controls sporulation in Physarum polycephalum. Photochem. Photobiol., 62(5):930–933, 1995.
  • [11] L. M. Torres and A. K. Wagler. Encoding the dynamics of deterministic systems. Math. Methods of Operations Research, 73:281–300, 2011.
  • [12] A. K. Wagler. Prediction of network structure. In I. Koch, F. Schreiber, and W. Reisig, editors, Modeling in Systems Biology, volume 16 of Computational Biology, pages 309–338. Springer London, 2010.
  • [13] A. K. Wagler and J.-T. Wegener. On minimality and equivalence of Petri nets. In CS&P, volume 928 of CEUR Workshop Proceedings, pages 382–393, 2012.
  • [14] A. K. Wagler and J.-T. Wegener. On minimality and equivalence of Petri nets. Fundamenta Informaticae, 128(1-2):209–222, 2013.
  • [15] A. K. Wagler and J.-T. Wegener. Preprocessing for network reconstruction: Feasibility test and handling infeasibility. In CS&P, volume 1032 of CEUR Workshop Proceedings, pages 434–447, 2013
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3c87e987-d2cc-4358-9bda-e6b54d16a2f8
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