Cel 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. Dziedzina nauki medical and health sciencesbasic medicinemedicinal chemistrynatural sciencescomputer and information sciencesartificial intelligencepattern recognitionnatural sciencesmathematicsapplied mathematicsstatistics and probabilitynatural sciencescomputer and information sciencesartificial intelligencemachine learning Program(-y) FP7-PEOPLE - Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) Temat(-y) FP7-PEOPLE-2010-IEF - Marie-Curie Action: "Intra-European fellowships for career development" Zaproszenie do składania wniosków FP7-PEOPLE-2010-IEF Zobacz inne projekty w ramach tego zaproszenia System finansowania MC-IEF - Intra-European Fellowships (IEF) Koordynator EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH Wkład UE € 170 401,60 Adres Raemistrasse 101 8092 Zuerich Szwajcaria Zobacz na mapie Region Schweiz/Suisse/Svizzera Zürich Zürich Rodzaj działalności Higher or Secondary Education Establishments Kontakt administracyjny Gisbert Schneider (Prof.) Linki Kontakt z organizacją Opens in new window Strona internetowa Opens in new window Koszt całkowity Brak danych
