Gaming and Data Mining in the Learning and Evaluation of Contacts in Biological Complexes

dc.creatorMarcos Felipe Martins Silva
dc.date.accessioned2019-11-22T18:18:28Z
dc.date.accessioned2025-09-09T01:05:45Z
dc.date.available2019-11-22T18:18:28Z
dc.date.issued2018-01-23
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
dc.identifier.urihttps://hdl.handle.net/1843/31231
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.rightsAcesso Aberto
dc.rightsAtribuição-SemDerivados 3.0 Portugal
dc.rights.urihttp://creativecommons.org/licenses/by-nd/3.0/pt/
dc.subject.otherGaming
dc.subject.otherData Mining
dc.subject.otherBioinformatics
dc.subject.otherContacts
dc.subject.otherBiological Complexes
dc.subject.otherNon-covalent Interatctions
dc.subject.otherDigital Games
dc.subject.otherDecision Trees
dc.titleGaming and Data Mining in the Learning and Evaluation of Contacts in Biological Complexes
dc.title.alternativeO Uso de Jogos e Mineração de Dados no Aprendizado e Avaliação de Contatos em Complexos Biológicos
dc.typeDissertação de mestrado
local.contributor.advisor-co1Cristiane Neri Nobre
local.contributor.advisor-co1http://lattes.cnpq.br/6608329267627163
local.contributor.advisor1Raquel Cardoso de Melo Minardi
local.contributor.advisor1Latteshttp://lattes.cnpq.br/9274887847308980
local.contributor.referee1Gisele Lobo Pappa
local.contributor.referee1Lucas Bleicher
local.creator.Latteshttp://lattes.cnpq.br/8640152999488456
local.description.resumoMolecules 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.
local.publisher.countryBrasil
local.publisher.departmentICX - DEPARTAMENTO DE CIÊNCIA DA COMPUTAÇÃO
local.publisher.initialsUFMG
local.publisher.programPrograma de Pós-Graduação em Ciência da Computação

Arquivos

Pacote original

Agora exibindo 1 - 1 de 1
Carregando...
Imagem de Miniatura
Nome:
Marcos_Silva_dissertation_ficha_catalografica.pdf
Tamanho:
8.48 MB
Formato:
Adobe Portable Document Format

Licença do pacote

Agora exibindo 1 - 1 de 1
Carregando...
Imagem de Miniatura
Nome:
license.txt
Tamanho:
2.07 KB
Formato:
Plain Text
Descrição: