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http://hdl.handle.net/10609/97847
Title: | Predictor de mutaciones patológicas para una familia de proteínas |
Author: | Salinero Delgado, Matías |
Tutor: | Andrio, Pau |
Abstract: | The development of the current biological techniques, such as sequencing and alignment, has provided us with a huge amount of data. This has highlighted the need to organize them and carry out an exhaustive and automatic study. A study that would allow us to better understand the obtained data and, as a result, discover the relationships that were hidden among them. The emergence of Machine Learning techniques opens up new possibilities like the detection of pathological mutations, as well as provide biomedical information that enables the development of therapies. The objective of this Master's Thesis is to develop an application to explore the benefits and limitations of this type of algorithms. It will display graphically and in a documented way the results achieved through a complete execution of the data cycle that will go from its import to the final result, tracking the performance throughout the process. |
Keywords: | machine learning Python proteins mutation |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | Jun-2019 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Appears in Collections: | Trabajos finales de carrera, trabajos de investigación, etc. |
Files in This Item:
File | Description | Size | Format | |
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msalinerodTFM0619memoria.pdf | Memoria del TFM | 3,83 MB | Adobe PDF | View/Open |
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