Opened Access Machine Learning: aplicación a datos RNA-Seq
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Autor: Fernández Delgado, Marta
Director: Cubiles de la Vega, María Dolores
Enguix González, Alicia
Departamento: Universidad de Sevilla. Departamento de Estadística e Investigación Operativa
Fecha: 2016-09
Tipo de documento: Trabajo Fin de Grado
Titulación: Universidad de Sevilla. Grado en Matemáticas
Resumen: Over the past years, biomedicine has experienced a revolution. This is partly due to the very high volume of information existing today that has been produced by both clinical and pharmacological studies as well as Omics data generation. At the same time, the development of statistical and computer techniques that allow its analysis has led to a new area of knowledge: Bioinformatics. The main aim of this study is to compare different Machine Learning techniques applied to a set of genetic data that were obtained through the RNA-Seq method. This method sequences cDNA in a massive way through a high-performance platform in order to gather global information about the DNA of a sample. Due to the efficacy, reproducibility and performance of the high-throughput sequencing, the RNA-Seq method allows researchers to measure the level of gene expression, detect alternative splicing, mutations, etc. It is also included in this study the theoretic and practical description of several supervised...
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Cita: Fernández Delgado, M. (201-). Machine Learning: aplicación a datos RNA-Seq. (Trabajo fin de grado inédito). Universidad de Sevilla, Sevilla.
Tamaño: 1.050Mb
Formato: PDF

URI: http://hdl.handle.net/11441/46276

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