Laetitia Gibart

Phd student in Computer Science
at Université Côte d'Azur.

My research interests are in the area of modelisation, Bioinformatics. I'm doing my PhD under the supervision of Pr. Jean-Paul Comet, Pr. Gilles Bernot and Dr. Hélène Collavizza. The title of my thesis is Discrete model life cycle and application to the regulation of pancreatic cancer cells.


Research interests

The modelling of complex biological systems does not benefit from the methods and tools that exist for the development of technological products in software engineering. The main reason for this is the impossibility of implementing a modular design: in biology, the introduction of a new element in a previously validated model can drastically change its behaviour. Nevertheless, this thesis provides an incremental methodology, in order to design discrete models for biology, which has some similarities to software spiral development model. The principal goal is to preserve the feasibility of proofs allowing to verify the non-regression at each enrichment. Although the proposed method was developed within the framework of René Thomas’ formalism, it can be adapted to any other discrete modelling framework. It includes three distinct phases: requirements analysis, model enrichment combined with validation by formal methods and finally a prediction phase. The substantial case study that anchors this work is a model of metabolic regulation at different stages of progression in pancreatic ductal adenocarcinoma (PDAC). In this work, we adopt an abstract modelling incremental approach, whose starting point is an already consequent general model of eukaryotic metabolic regulation. Our method allows us to enrich this initial model step by step to reach our aim, that is, a model covering the evolution from the healthy cell to the aggressive cell through the non-aggressive cancer cell. One has only little molecular a priori knowledge on the metabolic deregulation involved, and the level of abstraction of this model is chosen to best guide biologists in their research and in the choice of their working hypotheses.



  • A Phenotypic Matrix for Greening Qualitative Regulatory Networks with Environments
    L.Gibart; H.Collavizza; J-P.Comet, BMC Supplements
    -- (Accepted, 2022, 35pp)
  • Regulation of eukaryote metabolism: an abstract model.
    L. Gibart, R. Koodheraam, G. Bernot, J.-P.Comet, J.-Y. Trosset.
    -- Processes, Special Issue "Frontiers in Connecting Steady-State and Dynamic Approaches for Modelling Cell Metabolic Behavior", 2021, 26 pp DOI: 0.3390/pr9091496

Conference Papers

  • Greening R. Thomas' Framework with Environment Variables: a Divide and Conquer Approach ?
    L.Gibart, H. Collavizza and J.-P. Comet.
    -- CMSB'2021, 15pp + Appendices DOI: 10.1007/978-3-030-85633-5_3
  • TotemBioNet Enrichment Methodology: Application to the Qualitative Regulatory Network of the Cell Metabolism.
    L. Gibart, G. Bernot, H. Collavizza and J.P. Comet.
    BIOINFORMATICS 2021: 12th International Conference on Bioinformatics Models, Methods and Algorithms, online. 11--13 February, pp. 85--92, 2021.DOI: 10.5220/0010186200850092


Polytech Prépa intégrée

  • Programmation orienté objet, JAVA -- PEIP2 (équivalence L2)
  • Introduction au Web -- PEIP2 (équivalence L2)
  • Programation orienté objet, Python -- PEIP1 (équivalence L1)
  • Environnement informatique (linux) -- PEIP1 (équivalence L1)

Polytech Cycle ingénieur

  • IA, renforcement learning -- Sciences Informatiques 4 (équivalence M1)
  • Bonnes pratiques de la programmation, Python -- Génie Biologique 3 (équivalence L3)
  • Bases de donnée relationnelles -- Génie Biologique 4 (équivalence M1)
  • Bases de donnée relationnelles -- Génie Biologique 4 (équivalence M1)
  • Programation en langage de script-Python -- Génie Biologique 4 (équivalence M1)

Master Biologie Informatique et Mathématiques

  • Introduction à la bio-informatique par la programmation -- M1

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