Please use this identifier to cite or link to this item:

http://hdl.handle.net/10609/73785
Title: Machine learning para la predicción de interacciones entre microARN y ARN mensajeros
Author: Merino Monge, Manuel
Director: Morán Moreno, José Antonio
Tutor: Pla Planas, Albert
Others: Universitat Oberta de Catalunya
Keywords: feature selection
microRNA
sorters
machine learning
Issue Date: Jan-2018
Publisher: Universitat Oberta de Catalunya
Abstract: Micro RNA are small DNA sequence that manages gene expresion. A micro RNA matches in a specific binding site. The reason of this one is unknown. Several tools have been developed to predict these interactions. The goal of this project is developing a Java software based on machine learning and feature selection to classify two sequences (RNA and micro RNA) using Weka library. Data were extrated from public repositories. 18091 positive cases and 16711 negative cases were obtained. The result is a high accuracy of correct classification (86%). Several problems were presented during developing, so that number of features and classifiers were limited.
Language: Spanish
URI: http://hdl.handle.net/10609/73785
Appears in Collections:Bachelor thesis, research projects, etc.

Share:
Export:
Files in This Item:
File Description SizeFormat 
manmermonTFM0118memoria.pdfMemoria del TFM2.17 MBAdobe PDFView/Open

Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.