Ginsim

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.


References in zbMATH (referenced in 33 articles )

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  1. Moon, Kyungduk; Lee, Kangbok; Chopra, Sunil; Kwon, Steve: Bilevel integer programming on a Boolean network for discovering critical genetic alterations in cancer development and therapy (2022)
  2. Argyris, Georgios; Lluch Lafuente, Alberto; Tribastone, Mirco; Tschaikowski, Max; Vandin, Andrea: Reducing Boolean networks with backward Boolean equivalence (2021)
  3. Beneš, Nikola; Brim, Luboš; Pastva, Samuel; Šafránek, David: Aeon 2021: bifurcation decision trees in Boolean networks (2021)
  4. Macauley, Matthew; Youngs, Nora: The case for algebraic biology: from research to education (2020)
  5. Réda, Clémence; Wilczyński, Bartek: Automated inference of gene regulatory networks using explicit regulatory modules (2020)
  6. Sordo Vieira, Luis; Laubenbacher, Reinhard C.; Murrugarra, David: Control of intracellular molecular networks using algebraic methods (2020)
  7. Vladyslav Oles; Anton Kukushkin: BoolSi: A Tool for Distributed Simulations and Analysis of Boolean Networks (2020) not zbMATH
  8. Bernot, G.; Comet, J.-P.; Khalis, Z.; Richard, A.; Roux, O.: A genetically modified Hoare logic (2019)
  9. Crawford-Kahrl, Peter; Cummins, Bree; Gedeon, Tomas: Comparison of combinatorial signatures of global network dynamics generated by two classes of ODE models (2019)
  10. Macauley, Matthew; Jenkins, Andy; Davies, Robin: The regulation of gene expression by operons and the local modeling framework (2019)
  11. Menini, Laura; Possieri, Corrado; Tornambè, Antonio: Boolean network analysis through the joint use of linear algebra and algebraic geometry (2019)
  12. Richard, Adrien: Positive and negative cycles in Boolean networks (2019)
  13. Wery, Méline; Dameron, Olivier; Nicolas, Jacques; Remy, Elisabeth; Siegel, Anne: Formalizing and enriching phenotype signatures using Boolean networks (2019)
  14. Fauré, Adrien; Kaji, Shizuo: A circuit-preserving mapping from multilevel to Boolean dynamics (2018)
  15. Varela, Pedro L.; Lynce, Inês; Manquinho, Vasco; Chaouiya, Claudine; Monteiro, Pedro T.: Stable states of Boolean regulatory networks composed over hexagonal grids (2018)
  16. Jenkins, Andy; Macauley, Matthew: Bistability and asynchrony in a Boolean model of the \textscL-arabinose operon in \textitEscherichiacoli (2017)
  17. Matache, Mihaela T.; Matache, Valentin: Logical reduction of biological networks to their most determinative components (2016)
  18. Chaves, Madalena; Carta, Alfonso: Attractor computation using interconnected Boolean networks: testing growth rate models in \textitE. coli (2015)
  19. Zinovyev, A.: Overcoming complexity of biological systems: from data analysis to mathematical modeling (2015)
  20. Acary, Vincent; de Jong, Hidde; Brogliato, Bernard: Numerical simulation of piecewise-linear models of gene regulatory networks using complementarity systems (2014)

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