Deep Learning for Protein Function Prediction

dc.contributor	Cremers, Daniel
dc.contributor	Golkov, Vladimir
dc.contributor.author	Alba Avilés, Manuel
dc.date.accessioned	2018-06-01T10:25:31Z
dc.date.available	2018-06-01T10:25:31Z
dc.date.issued	2017-09-26
dc.identifier.uri	http://hdl.handle.net/2117/117716
dc.description.abstract	The assignment of functions to proteins is a bottleneck due to the need of costly and time-consuming molecular experiments. This is the reason why more often data analysis methods are used for protein an- notation. In this thesis I consider an approach based on Deep Learning architectures.
dc.language.iso	eng
dc.publisher	Universitat Politècnica de Catalunya
dc.subject	Àrees temàtiques de la UPC::Informàtica
dc.subject.lcsh	Machine learning
dc.subject.lcsh	Proteins
dc.subject.other	Biology
dc.subject.other	Data Science
dc.subject.other	Deep Learning
dc.subject.other	Machine Learning
dc.subject.other	Biologia
dc.title	Deep Learning for Protein Function Prediction
dc.title.alternative	Tiefe künstliche neuronal Netze für Vorhersage von Proteinfunktion
dc.type	Master thesis
dc.subject.lemac	Aprenentatge automàtic
dc.subject.lemac	Proteïnes
dc.identifier.slug	126454
dc.rights.access	Open Access
dc.date.updated	2017-12-23T05:00:19Z
dc.audience.educationlevel	Màster
dc.audience.mediator	Facultat d'Informàtica de Barcelona
dc.audience.degree	MÀSTER UNIVERSITARI EN INNOVACIÓ I RECERCA EN INFORMÀTICA (Pla 2012)
dc.contributor.covenantee	Technische Universität München

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