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Title: Machine learning i microRNAs: detecció i caracterització de potencials dianes en malalties neurodegeneratives
Author: Al-Dali Boada, Yasmina
Tutor: Pla Planas, Albert
Others: Prados Carrasco, Ferran  
Keywords: neurodegeneration
machine learning
Issue Date: Jan-2019
Publisher: Universitat Oberta de Catalunya (UOC)
Abstract: MiRNAs are single-stranded RNA molecules between 21 and 25 nucleotides, classified in the group of small non-coding RNAs. Since their discovery in the early 1990s, the study of these RNAs and their implications in gene regulation processes has not stopped growing. Today, it is known that miRNAs play an important role as suppressors of gene expression, and a single miRNA is capable of affecting the expression of hundreds of genes. Consequently, many routes and biological processes are affected by their action, including the development of pathologies. In this regard, research has been carried out mainly on different types of cancer, but it is known that the influence of miRNAs is also important in other diseases, such as neurodegenerative diseases. The present work focuses on the study of four of the main neurodegenerative diseases that currently affect the population: Alzheimer's, Amyotrophic Lateral Sclerosis, Multiple Sclerosis and Parkinson's. Through the application of machine learning techniques, an analysis of the possible interactions between a set of genes and miRNAs which have been differentially expressed in previous studies referring to these pathologies is performed. Of the genes identified as positive targets, ATR and TF prove to be common targets in the four diseases. By means of a functional study, these genes have been linked to the routes of the cell cycle, oxidative stress and ferroptosis, among others; results from which new lines of clinical research can be considered for the prevention and/or palliative therapy of these conditions.
Language: Catalan
Appears in Collections:Trabajos finales de carrera, trabajos de investigación, etc.

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