Literature DB >> 18372101

Petri net modelling of gene regulation of the Duchenne muscular dystrophy.

Stefanie Grunwald1, Astrid Speer, Jörg Ackermann, Ina Koch.   

Abstract

UNLABELLED: Searching for therapeutic strategies for Duchenne muscular dystrophy, it is of great interest to understand the responsible molecular pathways down-stream of dystrophin completely. For this reason we have performed real-time PCR experiments to compare mRNA expression levels of relevant genes in tissues of affected patients and controls. To bring experimental data in context with the underlying pathway theoretical models are needed. Modelling of biological processes in the cell at higher description levels is still an open problem in the field of systems biology. In this paper, a new application of Petri net theory is presented to model gene regulatory processes of Duchenne muscular dystrophy. We have developed a Petri net model, which is based mainly on own experimental and literature data. We distinguish between up- and down-regulated states of gene expression. The analysis of the model comprises the computation of structural and dynamic properties with focus on a thorough T-invariant analysis, including clustering techniques and the decomposition of the network into maximal common transition sets (MCT-sets), which can be interpreted as functionally related building blocks. All possible pathways, which reflect the complex net behaviour in dependence of different gene expression patterns, are discussed. We introduce Mauritius maps of T-invariants, which enable, for example, theoretical knockout analysis. The resulted model serves as basis for a better understanding of pathological processes, and thereby for planning next experimental steps in searching for new therapeutic possibilities. AVAILABILITY: Free availability of the Petri net editor and animator Snoopy and the clustering tool PInA via http://www-dssz.informatik.tu-cottbus.de/~ wwwdssz/. The Petri net models used can be accessed via http://www.tfh-berlin.de/bi/duchenne/.

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Year:  2008        PMID: 18372101     DOI: 10.1016/j.biosystems.2008.02.005

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  21 in total

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2.  A Stochastic Petri Net-Based Model of the Involvement of Interleukin 18 in Atherosclerosis.

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Journal:  Int J Mol Sci       Date:  2020-11-13       Impact factor: 5.923

3.  Simulation of a Petri net-based model of the terpenoid biosynthesis pathway.

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Journal:  BMC Bioinformatics       Date:  2010-02-09       Impact factor: 3.169

4.  Minimally perturbing a gene regulatory network to avoid a disease phenotype: the glioma network as a test case.

Authors:  Guy Karlebach; Ron Shamir
Journal:  BMC Syst Biol       Date:  2010-02-25

5.  Module detection in complex networks using integer optimisation.

Authors:  Gang Xu; Laura Bennett; Lazaros G Papageorgiou; Sophia Tsoka
Journal:  Algorithms Mol Biol       Date:  2010-11-12       Impact factor: 1.405

6.  Probabilistic polynomial dynamical systems for reverse engineering of gene regulatory networks.

Authors:  Elena S Dimitrova; Indranil Mitra; Abdul Salam Jarrah
Journal:  EURASIP J Bioinform Syst Biol       Date:  2011-06-06

7.  An enhanced Petri-net model to predict synergistic effects of pairwise drug combinations from gene microarray data.

Authors:  Guangxu Jin; Hong Zhao; Xiaobo Zhou; Stephen T C Wong
Journal:  Bioinformatics       Date:  2011-07-01       Impact factor: 6.937

8.  Comparison of evolutionary algorithms in gene regulatory network model inference.

Authors:  Alina Sîrbu; Heather J Ruskin; Martin Crane
Journal:  BMC Bioinformatics       Date:  2010-01-27       Impact factor: 3.169

9.  Modularization of biochemical networks based on classification of Petri net t-invariants.

Authors:  Eva Grafahrend-Belau; Falk Schreiber; Monika Heiner; Andrea Sackmann; Björn H Junker; Stefanie Grunwald; Astrid Speer; Katja Winder; Ina Koch
Journal:  BMC Bioinformatics       Date:  2008-02-08       Impact factor: 3.169

10.  MONALISA for stochastic simulations of Petri net models of biochemical systems.

Authors:  Pavel Balazki; Klaus Lindauer; Jens Einloft; Jörg Ackermann; Ina Koch
Journal:  BMC Bioinformatics       Date:  2015-07-10       Impact factor: 3.169

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