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INRA
24, chemin de Borde Rouge –Auzeville – CS52627
31326 Castanet Tolosan CEDEX - France

Dernière mise à jour : Mai 2018

Menu Logo Principal AgroParisTech Université Paris-Saclay

INRA GABI Unit

GABI : Génétique Animale et Biologie IntégrativeUnité Mixte de Recherche INRA - AgroParisTech

Frédéric HOSPITAL, Senior Research Scientist

HOSPITAL Frédéric
© INRA
My research is focused on modeling in theoretical genetics, at the interface between population genetics and quantitative genetics.

INRA UMR 1313 Génétique Animale et Biologie Intégrative
Domaine de Vilvert, Bat 211, 78352 Jouy en Josas
Tel : +33 (0) 1 34 65 21 69 Fax : +33 (0) 1 34 65 22 10

Email: frederic.hospital(at)jouy.inra.fr

Research Team : Population, Statistics and the Genome (PSGen)

Fields of Research :

Since my doctorate, I have been interested in complex genetic models including several loci associated genetically and undergoing selection. When I was recruited by INRA, I used both of these competencies to efficiently treat the emerging field of the use of molecular markers in selection programs. I worked in this field for several years, gaining original applied results while progressing in my understanding of the genetics of complex traits. Since then, I have returned to more theoretical studies in mathematics applied to problems of genetics, notably by collaborating with Theoretical Physicists.

Research Themes

Theory of Population Genetics, Quantitative Genetics and Selection Methodology.

1 - Modeling of the quantitative variation and evolution of complex traits. Identify the relevant, measurable parameters in order to improve our understanding of multiloci selection, the structure of selected polymorphisms and to predict responses to selection.

2 - Genetics of Chromosome Segments. Develop mathematical models for heredity in relation with modern genomics data : to describe Mendelian segregation in terms of blocks of several genes that are highly associated, or even continuous sequences instead of only loci that are few and/or isolated.

3 -Methodology for the Detection of Selective Sweeps in Experimental Populations. Develop the methods that can be applied on a smale time-scale and for a relatively strong selection (as compared to a weak selection on a long scale of evolution).

Publications and other recent projects :

http://fhospital.free.fr/fred/work/