Born: June 14, 1949, France
Present Status:
Former Associate Professor, INSERM 
Head, Biomathematics and Bioinformatics 
Department of Biological Hematology 
Innovative Biotherapies
CHRU Montpellier, Hopital Saint-Eloi
80, av. Augustin Fliche
34295 Montpellier - France
Tel.  +33 685 900 512
Education:
2001    Master in Bioinformatics (Montpellier II)
1984    Doctor of Sciences (Montpellier II)
1982    Pharmacy (Montpellier I)
1979    Certified in Oncology (Paris XI)
1979    Medicine (Montpellier I, Paris VI, VII, XI)
1972    Engineer (ENSCM Montpellier)
Research activities:
Assistant/Associate Professor, INSERM Units 236, 291, 475, 847 and 1040, Montpellier
Postdoctoral research, Ludwig Institute, Lausanne, Switzerland, JC Cerottini.
 Research project :
 Research project : 
The  aim of the department is to combine high throughput biological data (DNA  chips, Q-PCR, RNA-seq) and clinical data from documented patients to allow : 
- building classification tools for diagnosis, prognostic and  treatment response, starting from either recognized or personally  developed biomathematical methods
 - using such tools to predict classification and further therapeutic  indication of every new patient as well as extracting new therapeutic  targets from the data.
 Medical diagnosis (30% of activity) 
 A INSERM-CHU interface contract allowed the development of a web tool  http://rage.montp.inserm.fr with a friendly user interface for clinicians, allowing to filter, sort  and analyze data with supervised or unsupervised methods, to provide  dedicated files and links to other bioinformatics websites, to visualize  and graphically compare results and survival curves (relapse, death)in  selected cohorts, in the field of cancer (multiple myeloma, gliomas) as  well as for medically assisted reproduction. This platform also provides  quality control for the DNA chips processed in the Transcriptome  platform of IRB. 
 
 Basic research (70% of activity) : 
 The present web interface has become an undispensable day-to-day tool  for students and research groups using the IRB transcriptome platform  alltogether. By combining biological and clinical data, new methods are  currently developed to: 
- refine diagnosis process: more precise determination of clinical stages for a easier classification of new patients  
- select the best prognosis genes from survival data (event-free or overall) for an optimally adapted treatment 
 
- find new potential therapeutic targets from such prognosis genes 
 We have published the first predictive tool based on  simple presence or absence of expression of a gene list (BMC  Bioinformatics - 2008).
A prognosis stratification of multiple myeloma, breast cancer and glioma using our risk signature for overall survival (Bioinformatics - 2013) is available through the "Prognoweb" website: https://gliserv.montp.inserm.fr/
We recently published a molecular predictor able to classify gade II/III human gliomas with a much stronger prediction of outcome compared to the WHO grade II/III classification (Plos ONE - 2013)
Our tools are actualized with the last published developments. They allowed to establish numerous collaborative studies either locally (CHU, INM, IGF), nation-wide (Toulouse, Paris, Besançon) or internationally (Heidelberg, Germany, Rotterdam, Netherlands, Little Rock, USA).
