Automated experiment design for drug development

Examensarbete för masterexamen

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Bibliographical item details
Type: Examensarbete för masterexamen
Master Thesis
Title: Automated experiment design for drug development
Authors: Eriksson, Hannes
Abstract: Testing drugs in discovery is time consuming and expensive. An idea is then to eliminate unpromising compounds from the testing phase by using online learning methods to predict properties of yet to be tested compounds and determining which drugs to test. This is done by comparing substructures in the graph representation of compounds, transformed into a compressed high dimensional space where a Gaussian process bandit and a linear bandit is used to predict properties of new compounds. Results show that the bandits perform signi cantly better than random selection and that the feature compression probably does not decrease the overall accuracy of the predictions.
Keywords: Data- och informationsvetenskap;Informations- och kommunikationsteknik;Computer and Information Science;Information & Communication Technology
Issue Date: 2015
Publisher: Chalmers tekniska högskola / Institutionen för data- och informationsteknik (Chalmers)
Chalmers University of Technology / Department of Computer Science and Engineering (Chalmers)
Collection:Examensarbeten för masterexamen // Master Theses

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