Objetivo 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. Ámbito científico natural sciencesbiological sciencesdevelopmental biologynatural sciencesmathematicsapplied mathematicsstatistics and probabilitynatural sciencescomputer and information sciencesartificial intelligencemachine learning Programa(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) Tema(s) FP7-PEOPLE-2009-IEF - Marie Curie Action: "Intra-European Fellowships for Career Development" Convocatoria de propuestas FP7-PEOPLE-2009-IEF Consulte otros proyectos de esta convocatoria Régimen de financiación MC-IEF - Intra-European Fellowships (IEF) Coordinador EUROPEAN MOLECULAR BIOLOGY LABORATORY Aportación de la UE € 154 460,99 Dirección Meyerhofstrasse 1 69117 Heidelberg Alemania Ver en el mapa Región Baden-Württemberg Karlsruhe Heidelberg, Stadtkreis Tipo de actividad Research Organisations Contacto administrativo Tom Ratcliffe (Mr.) Enlaces Contactar con la organización Opens in new window Sitio web Opens in new window Coste total Sin datos Participantes (1) Ordenar alfabéticamente Ordenar por aportación de la UE Ampliar todo Contraer todo MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV La participación finalizó Alemania Aportación de la UE Sin datos Dirección HOFGARTENSTRASSE 8 80539 Munchen Ver en el mapa Región Bayern Oberbayern München, Kreisfreie Stadt Tipo de actividad Research Organisations Contacto administrativo Patrice Wegener (Mr.) Enlaces Contactar con la organización Opens in new window Sitio web Opens in new window Coste total Sin datos