Deep Neural Networks to find genetics signatures

Abstract

This document contais the final dissertation ot the degree student Fernando Moreno Jabato for the studies Grade in Health Engeneering, speciality on Bioinformatics, of University of Málaga. This dissertation have been performed with the supervision of Dr. José Manuel Jerez Aragonés from the Departament of Lenguajes y Ciencias de la Comunicación. The project title is Deep Neural Networks to find genetics signatures and is focused on the development of a bioinformatic tool oriented to identification of relationships between an attribute set and concret factor of interest on medicine. To do this, a tool was designed with the capacity of handle data sets from microarrays of diferent types. Microarrays was selected as preferent technology because it's the most extended and accessible techonologie on health and biology fields nowadays. Once implemented the tool, an experiment was performed to evaluate the effciency of this tool. The experiment uses prostate cancer related datasets from trascriptomics microarrays containing patients of prostate cancer and some normal individues. The results obtained in the experiment shows an improvement offered by the new Deep Learning algoritms (specifically, Deep Neural Networks) to analyze and obtain knowledgement from microarrays data. Besides, has been observed an improvement of efficiency and the beat of computational barriers that traditional Artifical Neural Networks suffered allowing apply this bioinformatics tools of new generation to masiva data sets.