Objectif Profound understanding of the relationship between molecular structure and biological activity is an essential prerequisite for rational drug design. Due to the inherent non-linearity of these relationships, ordinary regression is often inadequate, and black-box machine learning approaches offer limited, if any, interpretability. As a solution, we propose to use symbolic regression, in conjunction with a unique approach to feature selection, to establish quantitative structure-activity relationships (QSAR) that are succinct, non-linear, analytical, and interpretable. Symbolic regression is a stochastic optimization technique based on principles of evolution that searches the space of analytical expressions for equations that describe the investigated data. In other words, symbolic regression does not only fit the coefficients of an equation, but also the form of the equation itself. Our particular concept has not been used in QSAR before. We will combine theoretical investigations of the method with practical applications. Large combinatorial libraries will be analyzed to obtain validated QSAR models that are immediately and intuitively interpretable. Taking trypsin inhibition as an example, we will design, synthesize, and test new inhibitors suggested by our models. Our interdisciplinary project will contribute to European excellency in basic and applied pharmaceutical and medicinal chemistry, in line with health as a top priority of the seventh framework programme. Champ scientifique medical and health sciencesbasic medicinemedicinal chemistrynatural sciencescomputer and information sciencesartificial intelligencepattern recognitionnatural 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-2010-IEF - Marie-Curie Action: "Intra-European fellowships for career development" Appel à propositions FP7-PEOPLE-2010-IEF Voir d’autres projets de cet appel Régime de financement MC-IEF - Intra-European Fellowships (IEF) Coordinateur EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH Contribution de l’UE € 170 401,60 Adresse Raemistrasse 101 8092 Zuerich Suisse Voir sur la carte Région Schweiz/Suisse/Svizzera Zürich Zürich Type d’activité Higher or Secondary Education Establishments Contact administratif Gisbert Schneider (Prof.) Liens Contacter l’organisation Opens in new window Site web Opens in new window Coût total Aucune donnée