Thesis Details
Techniky klasifikace proteinů
Main goal of classifying proteins into families is to understand structural, functional and evolutionary relationships between individual proteins, which are not easily deducible from available data. Since the structure and function of proteins are closely related, determination of function is mainly based on structural properties, that can be obtained relatively easily with current resources. Protein classification is also used in development of special medicines, in the diagnosis of clinical diseases or in personalized healthcare, which means a lot of investment in it. I created a new hierarchical tool for protein classification that achieves better results than some existing solutions. The implementation of the tool was preceded by acquaintance with the properties of proteins, examination of existing classification approaches, creation of an extensive data set, realizing experiments and selection of the final classifiers of the hierarchical tool.
protein, amino acid, classification, neural net, SVM, random forest, feature vector
Lengál Ondřej, Ing., Ph.D. (DITS FIT BUT), člen
Orság Filip, Ing., Ph.D. (DITS FIT BUT), člen
Rogalewicz Adam, doc. Mgr., Ph.D. (DITS FIT BUT), člen
Veselý Vladimír, Ing., Ph.D. (DIFS FIT BUT), člen
@mastersthesis{FITMT21685,
author = "Luk\'{a}\v{s} Dekr\'{e}t",
type = "Master's thesis",
title = "Techniky klasifikace protein\r{u}",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2020,
location = "Brno, CZ",
language = "slovak",
url = "https://www.fit.vut.cz/study/thesis/21685/"
}