dc.contributor
Technische Universität München
dc.contributor
Cremers, Daniel
dc.contributor
Golkov, Vladimir
dc.contributor.author
Alba Avilés, Manuel
dc.date.issued
2017-09-26
dc.identifier
https://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.format
application/pdf
dc.publisher
Universitat Politècnica de Catalunya
dc.subject
Àrees temàtiques de la UPC::Informàtica
dc.subject
Machine learning
dc.subject
Machine Learning
dc.subject
Aprenentatge automàtic
dc.title
Deep Learning for Protein Function Prediction
dc.title
Tiefe künstliche neuronal Netze für Vorhersage von Proteinfunktion
