Gaming and Data Mining in the Learning and Evaluation of Contacts in Biological Complexes
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Universidade Federal de Minas Gerais
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Dissertação de mestrado
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O Uso de Jogos e Mineração de Dados no Aprendizado e Avaliação de Contatos em Complexos Biológicos
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Membros da banca
Gisele Lobo Pappa
Lucas Bleicher
Lucas Bleicher
Resumo
Molecules of life (carbohydrates, lipids, nucleic acids, and proteins) can change
their conformation in the space frequently due to non-covalent bonds (or contacts)
between their molecules. The comprehension of patterns created through the contacts
of atoms and amino acids has been used as an aid in solving a range of problems in
bioinformatics such as protein conformation, the functional similarities between proteins, structural alignment, thermodynamic stability prediction, prediction of protein
structures, drug design, and so forth. Several paradigms of calculation of contacts have
been developed. However, all models present advantages and disadvantages. The model
based only on distance present the problem of not guaranteeing that just the first layer
of neighbor atoms are connected by edges, and occlusions may occur (when there is an
intervening atom in-between). Concerning geometry, some techniques determine contacts in proteins through Delaunay and Voronoi tesselations. These methods present
an issue where two atoms could establish an interaction, but the unique triangulation
did not identify them as connected. Besides, the state-of-the-art lacks visualization
techniques of non-covalent interactions, what would highly help in the identification of
occlusions. An efficient manner to make the visualization of non-covalent interaction
is through the use of games due to its benefits such as pleasure, stimulation, creativity,
and enthusiasm. Also, several games in education have been an aid of understanding
open problems in biochemistry. Hence, the present dissertation proposes a methodology
for the construction and evaluation of a manually curated database for the classification of contacts between atoms of amino acids in protein chains through the use of
digital games. To evaluate the built database with the state-of-the-art, data mining
methods were used to find patterns in the classification of contacts. We also counted
on the participation of inexperienced players in biochemistry, and we have significant
evidence that they learned about molecular non-covalent bonds as they played.
Abstract
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Gaming, Data Mining, Bioinformatics, Contacts, Biological Complexes, Non-covalent Interatctions, Digital Games, Decision Trees
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