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Snoopy's bibliography - Beginner's Guide

latest update: April 27, 2019, at 02:27 AM


Please use the following reference to give credits to Snoopy:
M Heiner, M Herajy, F Liu, C Rohr and M Schwarick:
Snoopy – a unifying Petri net tool;
In Proc. PETRI NETS 2012, Hamburg, Springer, LNCS, volume 7347, 398–407, June 2012


This page contains recommendations where to start reading if you are new to the field, not necessarily in the given order.

i n d e x


. . . some helpful background knowledge . . .


  1. To get an overview in reasonable time, see

    [HG11]
    M Heiner and D Gilbert:
    How Might Petri Nets Enhance Your Systems Biology Toolkit;
    In Proc. PETRI NETS 2011, (Kristensen, LM and Petrucci, L, Eds.), Springer, pages 17–37, 2011. [ url ] [ pdf ] [ doi ] [ BibTeX ]
  2. To learn about the structured design of ODE's with continuous Petri nets, see

    [BGHO08]
    R Breitling, D Gilbert, M Heiner and R Orton:
    A structured approach for the engineering of biochemical network models, illustrated for signalling pathways;
    Briefings in Bioinformatics, 9(5):404–421, September 2008. [ doi ] [ BibTeX ]
  3. To understand why continuous Petri nets uniquely define ODE's, but not vice versa, see

    [SH10b]
    S Soliman and M Heiner:
    A Unique Transformation from Ordinary Differential Equations to Reaction Networks;
    PLoS ONE, 5(12):e14284, 2010. [ doi ] [ BibTeX ]
  4. To learn how structural analysis can complement insights gained by ODEs analysis, see

    [HS10]
    M Heiner and K Sriram:
    Structural Analysis to Determine the Core of Hypoxia Response Network;
    PLoS ONE, 5(1):e8600, 2010. [ doi ] [ BibTeX ]


. . . starting from scratch . . .


  1. For a start, take a quick look on framework overview
  2. For a gentle introduction into qualitative & stochastic Petri nets and their modelling and simulation with Snoopy, see

    [MRH12]
    W Marwan, C Rohr and M Heiner:
    Petri nets in Snoopy: A unifying framework for the graphical display, computational modelling, and simulation of bacterial regulatory networks;
    In Methods in Molecular Biology – Bacterial Molecular Networks, (Jv Helden, A Toussaint and D Thieffry, Eds.), Humana Press, pages 409–437, 2012. [ pdf ] [ doi ] [ BibTeX ]
  3. For an introduction into the core framework explaining - without any formal definitions - qualitative, stochastic and continuous Petri nets and their analysis using as running example the RKIP signalling pathway, see

    [HDG10]
    M Heiner, R Donaldson and D Gilbert:
    Petri Nets for Systems Biology;
    In Symbolic Systems Biology: Theory and Methods, (MS Iyengar, Ed.), Jones & Bartlett Learning, LCC, pages 61–97, 2010. [ url ] [ pdf ] [ BibTeX ]
  4. For a slightly extended introduction into the framework explaining - without any formal definitions - qualitative, stochastic, continuous and hybrid Petri nets in the uncoloured and coloured paradigms, using as running example the repressilator, see

    [LH14]
    F Liu and M Heiner:
    Petri Nets for Modeling and Analyzing Biochemical Reaction Networks;
    In Approaches in Integrative Bioinformatics, (M Chen and R Hofestädt, Eds.), Springer, pages 245–272, 2014. [ url ] [ pdf ] [ doi ] [ BibTeX ]
  5. For a rather exhaustive gentle introduction into the framework explaining - without any formal definitions - qualitative, stochastic, continuous and hybrid Petri nets in the uncoloured and coloured paradigms, using as running example Circadian oscillation, see

    [BHM15]
    MA Blätke, M Heiner and W Marwan:
    BioModel Engineering with Petri Nets;
    In Algebraic and Discrete Mathematical Methods for Modern Biology, (R Robeva, Ed.), Elsevier Inc., pages 141–193, March 2015. [ url ] [ doi ] [ BibTeX ]
  6. For a more comprehensive general introduction, including an explanation of the basic features of Snoopy and Charlie, see

    [BHM11]
    MA Blätke, M Heiner, and W Marwan:
    Tutorial - Petri Nets in Systems Biology;
    Technical report, Otto von Guericke University Magdeburg, Magdeburg Centre for Systems Biology, August 2011. [ pdf ] [ BibTeX ]


. . . more details . . .


  1. For more background information of the core framework providing also formal definitions and using as running example the MAPK signalling cascade, see

    [HGD08]
    M Heiner, D Gilbert and R Donaldson:
    Petri Nets for Systems and Synthetic Biology;
    In SFM 2008, (M Bernardo, P Degano and G Zavattaro, Eds.), Springer, pages 215–264, 2008. [ pdf ] [ doi ] [ BibTeX ]
  2. For a comprehensive discussion of Snoopy's stochastic Petri nets and their features, see

    [HLGM09]
    M Heiner, S Lehrack, D Gilbert and W Marwan:
    Extended Stochastic Petri Nets for Model-based Design of Wetlab Experiments;
    Transactions on Computational Systems Biology XI, 5750:138–163, 2009. [ url ] [ pdf ] [ doi ] [ BibTeX ]
  3. For a discussion of Snoopy's continuous and hybrid Petri nets and their features, see

    [HH12]
    M Herajy and M Heiner:
    Hybrid Representation and Simulation of Stiff Biochemical Networks;
    J. Nonlinear Analysis: Hybrid Systems, 6(4):942–959, November 2012. [ url ] [ doi ] [ BibTeX ]

    [HH17]
    Herajy, M and Heiner, M:
    Adaptive and Bio-semantics of Continuous Petri Nets: Choosing the Appropriate Interpretation;
    Fundamenta Informaticae, 160(1-2):53-80, 2018 (accepted: May 18, 2017). [ doi ] [ BibTeX ]

    [HH18]
    M Herajy and M Heiner:
    An Improved Simulation of Hybrid Biological Models with Many Stochastic Events and Quasi-Disjoint Subnets;
    In Proceedings of the 2018 Winter Simulation Conference (WSC 2018), Gothenburg, Sweden, IEEE, 978-1-5386-6572-5/18, pages 1346-1357, December 2018. [ url ] [ pdf ] [ doi ] [ BibTeX ]
  4. For a comprehensive discussion of Snoopy's continuous and hybrid Petri nets and their features, see

    [Herajy13]
    Mostafa Herajy:
    Computational Steering of Multi-Scale Biochemical Networks;
    PhD thesis, BTU Cottbus, Dep. of CS, January 2013. [ pdf ] [ BibTeX ]


. . . and then there was color . . .


  1. For a brief introduction into the colored framework, see

    [LH10]
    F Liu and M Heiner:
    Colored Petri nets to model and simulate biological systems;
    In Int. Workshop on Biological Processes & Petri Nets (BioPPN), satellite event of Petri Nets 2010, Braga, Portugal, pages 70-84, June 2010. [ pdf ] [ BibTeX ]
  2. For a more comprehensive description of the colored framework, see

    [Liu12]
    Fei Liu:
    Colored Petri Nets for Systems Biology;
    PhD thesis, BTU Cottbus, Dep. of CS, January 2012. [ pdf ] [ BibTeX ]
  3. For more details of Snoopy's colored Petri nets, see

    [LHR12.manual]
    F Liu, M Heiner and C Rohr:
    Manual for Colored Petri Nets in Snoopy;
    Technical report 02-12, Brandenburg University of Technology Cottbus, Department of Computer Science, March 2012. [ pdf ] [ BibTeX ]
  4. For dealing with reaction–diffusion systems using coloured Petri nets, see

    [LBHY14]
    F Liu, MA Blätke, M Heiner and M Yang:
    Modelling and simulating reaction–diffusion systems using coloured Petri nets;
    Computers in Biology and Medicine, 53:297–308, October 2014 (online July 2014). [ url ] [ doi ] [ BibTeX ]
  5. For some case studies deploying colored Petri nets, see Petri nets for multiscale Systems Biology


. . . modular modelling . . .


  1. To learn about modular modelling, see

    [BHM12]
    MA Blätke, M Heiner and W Marwan:
    Predicting Phenotype from Genotype Through Automatically Composed Petri Nets;
    In Proc. 10th International Conference on Computational Methods in Systems Biology (CMSB 2012), London, Springer, LNCS/LNBI, volume 7605, pages 87–106, 2012. [ url ] [ doi ] [ BibTeX ]
  2. For a modular model of JAK/STAT signalling, see

    [BDR+13]
    MA Blätke, A Dittrich, C Rohr, M Heiner, F Schaper and W Marwan:
    JAK/STAT signalling - an executable model assembled from molecule-centred modules demonstrating a module-oriented database concept for systems and synthetic biology;
    Molecular BioSystems, 9(6):1290-1307, 2013. [ url ] [ doi ] [ BibTeX ]
  3. To play with our database prototype for modular modelling in systems and synthetic biology, go to

    BioModelKit website

… the end …

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