Yannick DE OLIVEIRA
Ingénieur d'Études, INRAE
Programming & framework, DBMS & NoSQL Technologies
yannick.de-oliveira@inrae.fr
01 69 33 23 76
- Génétique Quantitative et Évolution - Le Moulon
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech
- Ferme du Moulon
- F-91190 Gif-sur-Yvette
-
Équipes :
- ABI
Education and positions
- BioInformatics engineer (2009-…), Java/Python-Django SHiNeMaS and BioMercator projects, INRA
- Head of development (2007-2009), Java-J2EE/Python-Django development and customer support of a LIMS solution, Sibio
- BioInformatics engineer (2004-2007), Java/Perl developer on FLAGdb++ and UTILLd, INRA
- Master degree in BioInformatics (2004) « Etude de Génomes Outils Informatiques et Statistiques », Rouen.
Current projects
I’m at head of two development projects in the team:
- SHiNeMaS (Seeds History and network Management System), a database dedicated to seed lots history, phenotyping data and field practices,
- BioMercato, a complete framework to integrate QTL, meta-QTL, genome annotation and genome-wide association studies.
I’m also involved in other development projects:
- Thaliadb, A database dedicated to association genetic in plants,
- Bakery, an ANR project focused on diversity and interactions in a low-input « Wheat/Human/Sourdough » agro-food ecosystem in which I develop a new database.
Skills
| xx | yy |
|---|---|
| Programming & framework | Python – Django, Java – Spring & Hibernate, Perl – BioPerl - Javascript, Jquery, HTML |
| DBMS & NoSQL Technologies | PostgreSQL, Oracle, Mongodb |
Publications
- De Oliveira Y. , Burlot L., Dawson JC., Goldringer I., Madi D., Rivière P., Steinbach D., van Frank G., Thomas M.. (2020) SHiNeMaS: a web tool dedicated to seed lots history, phenotyping and cultural practices. Plant Methods, 1 (16) 98
- Lopez Arias DC., Chastellier A., Thouroude T., Bradeen J., Van Eck L., De Oliveira Y. , Paillard S., Foucher F., Hibrand-Saint Oyant L., Soufflet-Freslon V.. (2020) Characterization of black spot resistance in diploid roses with QTL detection, meta-analysis and candidate-gene identification. Theor Appl Genet,