Objectif Understanding phenotypic variation, and more particularly identifying the causal genetic or environmental regulators, is a major aim in biological investigations. The goal of this proposal is to develop and apply machine learning techniques to model key aspects of structure that occur in modern, high-dimensional phenotype datasets. First, the temporal structure of phenotypes that are recorded over time is addressed. Statistical models can exploit smoothness of time series and detect change points. Second, the structure of images, arising when digital pictures are used as phenotypic variables, is considered. Machine learning techniques allow interpretable image features to be automatically extracted and used as quantitative traits, complementing classical measurements. Finally, the network structure of the phenome is addressed. Different phenotype variables influence each other, resulting in a chain of effects that needs to be modelled to reveal the true causal relationships. The developed algorithms will be applied to understand phenotypic variation in Arabidopsis thaliana in direct collaboration with researchers at the Max Planck Institute for Developmental Biology. Champ scientifique natural sciencesbiological sciencesdevelopmental biologynatural sciencesmathematicsapplied mathematicsstatistics and probabilitynatural sciencescomputer and information sciencesartificial intelligencemachine learning Programme(s) FP7-PEOPLE - Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) Thème(s) FP7-PEOPLE-2009-IEF - Marie Curie Action: "Intra-European Fellowships for Career Development" Appel à propositions FP7-PEOPLE-2009-IEF Voir d’autres projets de cet appel Régime de financement MC-IEF - Intra-European Fellowships (IEF) Coordinateur EUROPEAN MOLECULAR BIOLOGY LABORATORY Contribution de l’UE € 154 460,99 Adresse Meyerhofstrasse 1 69117 Heidelberg Allemagne Voir sur la carte Région Baden-Württemberg Karlsruhe Heidelberg, Stadtkreis Type d’activité Research Organisations Contact administratif Tom Ratcliffe (Mr.) Liens Contacter l’organisation Opens in new window Site web Opens in new window Coût total Aucune donnée Participants (1) Trier par ordre alphabétique Trier par contribution de l’UE Tout développer Tout réduire MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV Participation terminée Allemagne Contribution de l’UE Aucune donnée Adresse HOFGARTENSTRASSE 8 80539 Munchen Voir sur la carte Région Bayern Oberbayern München, Kreisfreie Stadt Type d’activité Research Organisations Contact administratif Patrice Wegener (Mr.) Liens Contacter l’organisation Opens in new window Site web Opens in new window Coût total Aucune donnée