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Title: Creación de una herramienta de software para predecir la interacción, actividad y función de fármacos
Author: Jiménez Hernández, Hugo
Director: Marco-Galindo, Maria-Jesús  
Tutor: Sanchez-Martinez, Melchor  
Others: Universitat Oberta de Catalunya
Abstract: The drug discovery process for the treatment of diseases is wide and complex area in constant evolution. Today is known that multiple factors are responsible for triggering pathogenesis (environment, physiology, genetics...). This greatly influence the development of pharmacological treatments and hence, as of late, there have been a trend on personalized treatments by means of several disciplines like polypharmacology, pharmacogenomics, etc. This customized treatments yields a large amount of data which cannot be processed in a conventional way. Therefore, it is necessary to use Big Data mining and Machine Learning techniques. The present work aims to develop a tool that does a similarity search (virtual screening) of a given molecule against an specially curated database built from other compounds databases and, in a second stage, try to predict by means of Machine Learning algorithms active compounds for a given target.
Keywords: predictions
Document type: info:eu-repo/semantics/masterThesis
Issue Date: Jan-2018
Publication license:  
Appears in Collections:Trabajos finales de carrera, trabajos de investigación, etc.

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