Nolwenn LE MEUR

Nolwenn LE MEUR

Avenue du Professeur Léon-Bernard CS 74312 - 35043 - Rennes

Tel: +33 (0) 2 99 02 25 14 (work)

E-mail: (work)

Current position: Associate Professor

Affiliation(s): Département Méthodes quantitatives en santé publique (METIS)


1997-2000 : Engineer in microbiology and food safety, Ecole Supérieure de Microbiologie et Sécurité Alimentaire de Brest (ESMISAB), Université de Bretagne Occidentale, Brest, France.
2000-2001 : Master in Genomic and bioinformatic , Université de Haute Bretagne, Rennes I, France.
2001-2005 : PhD in Bioinformatic, INSERMU533,  Université de Loire Atlantique, Nantes, France.
Juillet 2005 – Février 2008 : Post-doctorat - Fred Hutchinson Cancer Research Center Seattle, WA - USA
Dr R. Gentleman's team, Public Health Science, Computational Biology group.
Mars 2008 – Octobre 2010 : Post-Doctorat - IRISA INSERM - Université de Rennes I.
Dr N. Théret's team, UPRES SeRAIC INSERM - Université de Rennes I.
Mars 2010 - Octobre 2010 : Integrative genomics - Project coordinator - Biogenouest


My background is in bioinformatics and computational biology .

In computational biology, I have developed graph methods and models to analyze cellular interactions and better understand their role in determining phenotype.

  • integrating high throughput proteomic data and graph theoretic approaches to decipher the role of protein complexes in yeast.
  • modeling signaling pathways at the system level to better understand the regulatory mechanisms.

My work in bioinformatics has mainly been on data quality assessment and data mining for:

  •  microarray analysis (
  • flow cytometry standardization and analaysis (FlowCore suite on
  • cell-based assays (siRNA high throughput screen).

Recently,  I got interested in the field of Biostatistics and Public health science. There is so much data in Public health that are underemployed and that would benefit population health in terms of services, policies, environment. I am currently using data mining and graph theory approach on health administrative information systems to explore care trajectories of patient to study :

  • access to care in relation with there socio-economic environment (DISPARITE project financed by EHESP; Projet AGIR project financed by USPC)
  • care facilities relationship   (financed by FEHAP),
  • identify never events associated to surgery of in- and -outpatients (PEPS project financed by ANSM; PRINCEPS project financed by USPC)


R language

Analysis of French medico-administrative databases (PMSI, SNIIRAM)
Analysis of  *omics data  (microarray, flow cytometry, siRNA)


  • R language
  • Biostatistics
    • Master of Public Health (FR ; EN)
    • Health care institute managers
    • Public health professional
    • IDEA (Field training for epidemiologists)