Conformational B-Cell epitope prediction

Examensarbete för masterexamen

Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12380/245105
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Type: Examensarbete för masterexamen
Master Thesis
Title: Conformational B-Cell epitope prediction
Authors: Ström, Fredrik
Abstract: There is demand for higher quality therapeutic proteins in our society. Medical drug developing companies strive for lower development cost and shorter development time. This require faster and more reliable ways of testing the therapeutic proteins before releasing them to the public. This project aimed to investigate one part of this problem, the conformational B-cell epitopes which is the interface between an foreign molecule (antigen) and an antibody. It was done by development of two different epitope models, which then was used as a base for creation of two training data sets. These training sets were then used to train machine learning algorithms in order to classify areas on molecule surfaces which are prone to be an epitope. Different problems in this research area is discussed and possible solutions is proposed.
Keywords: Informations- och kommunikationsteknik;Data- och informationsvetenskap;Information & Communication Technology;Computer and Information Science
Issue Date: 2016
Publisher: Chalmers tekniska högskola / Institutionen för data- och informationsteknik (Chalmers)
Chalmers University of Technology / Department of Computer Science and Engineering (Chalmers)
URI: https://hdl.handle.net/20.500.12380/245105
Collection:Examensarbeten för masterexamen // Master Theses



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