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Strojové učení v úloze predikce vlivu nukleotidového polymorfismu / Prediction of the Effect of Nucleotide Substitution Using Machine Learning

This thesis brings a new approach to the prediction of the effect of nucleotide polymorphism on human genome. The main goal is to create a new meta-classifier, which combines predictions of several already implemented software classifiers. The novelty of developed tool lies in using machine learning methods to find consensus over those tools, that would enhance accuracy and versatility of prediction. Final experiments show, that compared to the best integrated tool, the meta-classifier increases the area under ROC curve by 3,4 in average and normalized accuracy is improved by up to 7\,\%. The new classifying service is available at http://ll06.sci.muni.cz:6232/snpeffect/.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:234918
Date January 2015
CreatorsŠalanda, Ondřej
ContributorsMartínek, Tomáš, Bendl, Jaroslav
PublisherVysoké učení technické v Brně. Fakulta informačních technologií
Source SetsCzech ETDs
LanguageCzech
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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