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Christine Froidevaux

Email chris at lri . fr
Home page
Position Professor emeritus at the University Paris-Saclay (Orsay)
Phone +33 1 69 15 65 07
FAX +33 1 69 15 65 86
Office 172
AddressLRI - Ada Lovelace building
University Paris-Saclay
F-91405 Orsay Cedex France

Professor emeritus in Computer Science at the University of Paris Saclay, member of the Bioinformatics group at the Laboratory of Computer Science LRI/LISN.



  • Genome Bioinformatics
    • Integration of data from biomedical data sources and knowledge extraction in genomic data sources
    • Systems biology: design and analysis of biological networks
  • Computational methods
    • Integrating and querying data sources; ontologies mapping
    • Scientific workflows
    • Data extraction and Knowledge-based reasoning


ANR ABLISS : Automating Building from Literature of Signalling Systems

  • PhD theses

    • Data science for biological signalling networks (Aziza Filali Rotbi, co-supervised by Nicole Bidoit and Philippe Chatalic, LRI)
    • A logical approach to the systematic identification of computational network models for predicting synergistic genetic interactions involved in tumoral proliferation (Stéphanie Chevalier, co-supervised with Loïc Paulevé, LaBRI, and Andrei Zinovyev, Institut Curie)
    • Reconstruction of metabolic networks by functional annotation and completion of these networks by integration of heterogeneous data (Alexandra Zaharia, co-supervised with Alain Denise, PhD defended on Sept. 2018)
    • Qualitative methods for designing and analysing SBGN molecular networks (Adrien Rougny, in collaboration with Anne Poupon, INRA BIOS, PhD defended on Oct. 2016)
    • Designing scientific workflows following a structure and provenance-aware strategy (Jiuqiang Chen, co-supervised with Sarah Cohen-Boulakia, PhD defended on Oct. 2013)


List of selected publications.


  • M Sc Bioinformatics (Master M1 BIBS and M2 AMI2B)
    • Data Bases
    • Algorithmics
    • Introduction to Data Mining
    • Integration of heterogeneous data sources and Big Data

  • Teacher training in mathematics, track on computer science