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MODAL - 2018
Overall Objectives
Application Domains
New Results
Bibliography
Overall Objectives
Application Domains
New Results
Bibliography


Section: Partnerships and Cooperations

Regional Initiatives

Bilille partnership

Participant : Guillemette Marot.

Bilille, the bioinformatics platform of Lille, officially gathers from Nov. 2015 a few bioinformaticians, biostatisticians and bioanalysts from the following teams:

  • EA2694 (Univ. Lille, CHRU, Inria)

  • FRABIO, FR3688 (Univ. Lille,CNRS)

  • CBP / GFS (Univ. Lille, CHRU)

  • TAG (Univ. Lille, CNRS, INSERM, Institut Pasteur de Lille)

  • U1167 (Univ. Lille, CHRU, INSERM et Institut Pasteur de Lille)

  • U1011 (Univ. Lille, INSERM)

  • UMR8198 (Univ. Lille, CNRS)

  • LIGAN PM (Univ. Lille, CNRS)

  • BONSAI (Inria, Univ. Lille, CNRS).

These last teams are thus the main partners of Modal concerning biostatistics for bioinformatics. Guillemette Marot is the co-head of the platform and works in close collaboration with the following people for the leadership of the scientific strategy related to the platform:

  • H. Touzet, BONSAI, UMR 9189 (co-head of bilille)

  • P. Touzet, UMR 8198 (deputy head of bilille)

  • C. Bellenguez, U1167

  • M. Figeac, CBP / GFS

  • D. Hot, TAG

  • V. Leclère, Insitut Charles Viollette

  • M. Lensink, UMR 8576.

  • O. Sand, IFB-Core.

Bilille collaborations

Participants : Guillemette Marot, Vincent Vandewalle.

Guillemette Marot and Vincent Vandewalle have supervised the data analysis part or support in biostatistics tools testing for the following research projects involving engineers from bilille (only the names of the principal investigators of the project are given even if several partners are sometimes involved in the project):

  • CIIL, C. Faveeuw, Analysis of cytometry data

  • CIIL, P. Brodin, Analysis of phenotypic screening data

  • JPARC, J.M. Taymans, Analysis of translation chips

  • JPARC, M.C. Chartier-Harlin, RNA-Seq meta-analysis

  • JPARC, A. Vincent, Microarray analysis

  • UMR 1167, F. Pinet, Analysis of proteomic data.