Neural Networks for Subcellular Localization Prediction

Machine Learning

Friday, the 15 of December, 2017

Citation (APA)

Fontal, A. (2017). Neural Networks for Subcellular Localization Prediction.


The continuously decreasing cost of sequencing genomes is promoting the generation of vast amounts of sequence data. In consequence, the need to develop automated methods of analysis for this kind of data is on the rise. A first step towards inferring a protein’s function is to know its subcellular location. In this thesis we explore the capabilities of modern machine learning techniques, and more specifically deep learning models to predict the subcellular location of proteins only using their amino acid sequence as predictor.