GINsim: A software suite for the qualitative modelling, simulation and analysis of regulatory networks. This paper presents GINsim, a Java software suite devoted to the qualitative modelling, analysis and simulation of genetic regulatory networks. Formally, our approach leans on discrete mathematical and graph-theoretical concepts. GINsim encompasses an intuitive graph editor, enabling the definition and the parameterisation of a regulatory graph, as well as a simulation engine to compute the corresponding qualitative dynamical behaviour. Our computational approach is illustrated by a preliminary model analysis of the inter-cellular regulatory network activating Notch at the dorsal–ventral boundary in the wing imaginal disc of Drosophila. We focus on the cross-regulations between five genes (within and between two cells), which implements the dorsal–ventral border in the developing imaginal disc. Our simulations qualitatively reproduce the wild-type developmental pathway, as well as the outcome of various types of experimental perturbations, such as loss-of-function mutations or ectopically induced gene expression.

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  1. Macauley, Matthew; Youngs, Nora: The case for algebraic biology: from research to education (2020)
  2. Réda, Clémence; Wilczyński, Bartek: Automated inference of gene regulatory networks using explicit regulatory modules (2020)
  3. Sordo Vieira, Luis; Laubenbacher, Reinhard C.; Murrugarra, David: Control of intracellular molecular networks using algebraic methods (2020)
  4. Vladyslav Oles; Anton Kukushkin: BoolSi: A Tool for Distributed Simulations and Analysis of Boolean Networks (2020) not zbMATH
  5. Bernot, G.; Comet, J.-P.; Khalis, Z.; Richard, A.; Roux, O.: A genetically modified Hoare logic (2019)
  6. Crawford-Kahrl, Peter; Cummins, Bree; Gedeon, Tomas: Comparison of combinatorial signatures of global network dynamics generated by two classes of ODE models (2019)
  7. Macauley, Matthew; Jenkins, Andy; Davies, Robin: The regulation of gene expression by operons and the local modeling framework (2019)
  8. Menini, Laura; Possieri, Corrado; Tornambè, Antonio: Boolean network analysis through the joint use of linear algebra and algebraic geometry (2019)
  9. Richard, Adrien: Positive and negative cycles in Boolean networks (2019)
  10. Wery, Méline; Dameron, Olivier; Nicolas, Jacques; Remy, Elisabeth; Siegel, Anne: Formalizing and enriching phenotype signatures using Boolean networks (2019)
  11. Fauré, Adrien; Kaji, Shizuo: A circuit-preserving mapping from multilevel to Boolean dynamics (2018)
  12. Jenkins, Andy; Macauley, Matthew: Bistability and asynchrony in a Boolean model of the \textscL-arabinose operon in \textitEscherichiacoli (2017)
  13. Matache, Mihaela T.; Matache, Valentin: Logical reduction of biological networks to their most determinative components (2016)
  14. Chaves, Madalena; Carta, Alfonso: Attractor computation using interconnected Boolean networks: testing growth rate models in \textitE. coli (2015)
  15. Zinovyev, A.: Overcoming complexity of biological systems: from data analysis to mathematical modeling (2015)
  16. Acary, Vincent; de Jong, Hidde; Brogliato, Bernard: Numerical simulation of piecewise-linear models of gene regulatory networks using complementarity systems (2014)
  17. Bérenguier, D.; Chaouiya, C.; Monteiro, P. T.; Naldi, A.; Remy, E.; Thieffry, D.; Tichit, L.: Dynamical modeling and analysis of large cellular regulatory networks (2013)
  18. Thomas, R.: Remarks on the respective roles of logical parameters and time delays in asynchronous logic: an homage to El Houssine Snoussi (2013)
  19. Veliz-Cuba, Alan; Buschur, Kristina; Hamershock, Rose; Kniss, Ariel; Wolff, Esther; Laubenbacher, Reinhard: AND-NOT logic framework for steady state analysis of Boolean network models (2013)
  20. Chaouiya, C.; Naldi, A.; Remy, E.; Thieffry, D.: Petri net representation of multi-valued logical regulatory graphs (2011)

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