Research Interests:
Tratamos aqui uma pesquisa em andamento sobre os cursos de formação pedagógica para os docentes graduados não licenciados dos institutos federais. Por meio de um estudo de caso, utilizando-se de análise documental dos projetos pedagógicos... more
Tratamos aqui uma pesquisa em andamento sobre os cursos de formação pedagógica para os docentes graduados não licenciados dos institutos federais. Por meio de um estudo de caso, utilizando-se de análise documental dos projetos pedagógicos destes cursos, esta pesquisa tem por objetivo analisar as propostas de licenciatura direcionadas à formação do magistério para atuarem na educação profissional no que diz respeito à concepção pedagógica de ensino integrado presente em seus textos. Tal estudo justifica-se pela intenção em descrever o cenário de formação proposto pelos IF aos seus professores não licenciados. Os resultados preliminares apontam que os projetos negligenciam temas como trabalho como princípio educativo, interdisciplinaridade, contextualização e transformação da realidade social, considerados elementos orientadores em práticas pedagógico-curriculares integradoras.Palavras-chave: Formação docente. Educação profissional. Currículo integrado.
Complex networks have been successfully applied to the characterization and modeling of complex systems in several distinct areas of Biological Sciences. Nevertheless, their utilization in phylogenetic analysis still needs to be widely... more
Complex networks have been successfully applied to the characterization and modeling of complex systems in several distinct areas of Biological Sciences. Nevertheless, their utilization in phylogenetic analysis still needs to be widely tested, using different molecular data sets and taxonomic groups, and, also, by comparing complex networks approach to current methods in phylogenetic analysis. In this work, we compare all the four main methods of phylogenetic analysis (distance, maximum parsimony, maximum likelihood, and Bayesian) with a complex networks method that has been used to provide a phylogenetic classification based on a large number of protein sequences as those related to the chitin metabolic pathway and ATP-synthase subunits. In order to perform a close comparison to these methods, we selected Basidiomycota fungi as the taxonomic group and used a high-quality, manually curated and characterized database of chitin synthase sequences. This enzymatic protein plays a key ro...
Research Interests:
Research Interests: Bioinformatics, Computer Science, Algorithms, Computational Biology, Biology, and 15 moreComplex Networks, Medicine, Biological Sciences, Enzymes, Mathematical Sciences, Complex network, Archaea, Bacteria, Enzyme, Network structure, Metabolic pathway, Eukaryotic Cells, Amino Acid Sequence, Bayes Theorem, and Chitin
Research Interests: Engineering, Bioinformatics, Data Mining, Comparative Genomics, A Priori Knowledge, and 15 moreComplex Networks, Biological Sciences, Higher Order Thinking, Computer Simulation, Complex network, Archaea, Bacteria, Meta Analysis, Metabolic pathway, Biosystems, Amino Acid Sequence, Cell Wall, Elsevier, Chitin, and Higher order
Resumo: O presente trabalho teve como objetivo apresentar uma proposta para integrar o desenvolvimento de Objetos de Aprendizagem com os elementos da mecânica dos jogos. Inicialmente, verificamos a potencialidade que existe, isoladamente,... more
Resumo: O presente trabalho teve como objetivo apresentar uma proposta para integrar o desenvolvimento de Objetos de Aprendizagem com os elementos da mecânica dos jogos. Inicialmente, verificamos a potencialidade que existe, isoladamente, nos conceitos de Objetos de Aprendizagem e de Gamificação e percebemos que a união desses dois objetos de estudo traria grandes benefícios para o ensino de ciências. Após realizar uma pesquisa bibliográfica, constatamos que não existe um modelo formal que unifique esses dois conceitos. Devido a isso, construímos um diagrama que serve como ponte de ligação entre eles, tendo como base um modelo de desenvolvimento de Objetos de Aprendizagem e publicações dos principais autores na área de gamificação e game designer. Por fim, apresentamos um roteiro que norteia o desenvolvimento de Objetos de Aprendizagem Gamificados. Os resultados obtidos evidenciaram o caráter pedagógico e interdisciplinar do modelo, das referências e dos diagramas apresentados neste...
Research Interests:
Este artigo apresenta um modelo e um protocolo com objetivo de nortear o processo de desenvolvimento de jogos digitais. A metodologia do estudo é de natureza qualitativa. Neste trabalho mesclamos referências da área de designer de jogos... more
Este artigo apresenta um modelo e um protocolo com objetivo de nortear o processo de desenvolvimento de jogos digitais. A metodologia do estudo é de natureza qualitativa. Neste trabalho mesclamos referências da área de designer de jogos digitais, gamificação e protolocos que serviram como base estrutural das nossas sugestões. O resultado final dessa investigação possibilitou a construção de um modelo cuja aplicação potencializa especialização de metodologias e frameworks de desenvolvimento de jogos digitais. Palavras-chave: Modelo, protocolo, desarrollo, descrición, juegos digitales.
Research Interests:
Research Interests:
Research Interests:
O presente trabalho teve como objetivo apresentar uma proposta para integrar o desenvolvimento de Objetos de Aprendizagem com os elementos da mecânica dos jogos. Inicialmente, verificamos a potencialidade que existe, isoladamente, nos... more
O presente trabalho teve como objetivo apresentar uma proposta para integrar o desenvolvimento de Objetos de Aprendizagem com os elementos da mecânica dos jogos. Inicialmente, verificamos a potencialidade que existe, isoladamente, nos conceitos de Objetos de Aprendizagem e de Gamificação e percebemos que a união desses dois objetos de estudo traria grandes benefícios para o ensino de ciências. Após realizar uma pesquisa bibliográfica, constatamos que não existe um modelo formal que unifique esses dois conceitos. Devido a isso, construímos um diagrama que serve como ponte de ligação entre eles, tendo como base um modelo de desenvolvimento de Objetos de Aprendizagem e publicações dos principais autores na área de gamificação e game designer. Por fim, apresentamos um roteiro que norteia o desenvolvimento de Objetos de Aprendizagem Gamificados. Os resultados obtidos evidenciaram o caráter pedagógico e interdisciplinar do modelo, das referências e dos diagramas apresentados neste trabalho. Acreditamos que iniciativas como essa favorecem o desenvolvimento de componentes pedagógicos que possibilitam o estudo de aspectos imperceptíveis aos alunos, quando analisados através de recursos tradicionais como o livro e apostilas.
Research Interests:
Research Interests: Bioinformatics, Algorithms, Computational Biology, Complex Networks, Modularity (Evolution), and 19 moreSignal Transduction, Biological Sciences, Phylogeny, Enzymes, Mathematical Sciences, Complex network, Archaea, Bacteria, Phylogenetic analysis, Enzyme, Protein Sequence Analysis, Network Topology, Network structure, Metabolic pathway, Eukaryotic Cells, Amino Acid Sequence, Bayes Theorem, Chitin, and Similarity Index
Chitin is a structural endogenous carbohydrate, which is a major component of fungal cell walls and arthropod exoskeletons. A renewable resource and the second most abundant polysaccharide in nature after cellulose, chitin is currently... more
Chitin is a structural endogenous carbohydrate, which is a major component of fungal cell walls and arthropod exoskeletons. A renewable resource and the second most abundant polysaccharide in nature after cellulose, chitin is currently used for waste water clearing, cosmetics, medical, and veterinary applications. This work comprises data mining of protein sequences related to the chitin metabolic pathway
of completely sequenced genomes of extant organisms pertaining to the three life domains, followed by
meta-analysis using traditional sequence similarity comparison and complex network approaches. Complex
networks involving proteins of the chitin metabolic pathway in extant organisms were constructed based on protein sequence similarity. Several usual network indices were estimated in order to obtain information on the topology of these networks, including those related to higher order neighborhood properties. Due to the assumed evolutionary character of the system, we also discuss issues related to modularity properties, with the concept of edge betweenness playing a particularly important role in our analysis. Complex network approach correctly identifies clusters of organisms that belong to phylogenetic groups without any a priori knowledge about the biological features of the investigated protein sequences. We envisage the prospect of using such a complex network approach as a high-throughput phylogenetic method.
of completely sequenced genomes of extant organisms pertaining to the three life domains, followed by
meta-analysis using traditional sequence similarity comparison and complex network approaches. Complex
networks involving proteins of the chitin metabolic pathway in extant organisms were constructed based on protein sequence similarity. Several usual network indices were estimated in order to obtain information on the topology of these networks, including those related to higher order neighborhood properties. Due to the assumed evolutionary character of the system, we also discuss issues related to modularity properties, with the concept of edge betweenness playing a particularly important role in our analysis. Complex network approach correctly identifies clusters of organisms that belong to phylogenetic groups without any a priori knowledge about the biological features of the investigated protein sequences. We envisage the prospect of using such a complex network approach as a high-throughput phylogenetic method.
Research Interests:
This paper proposes a new method to identify communities in generally weighted complex networks and apply it to phylogenetic analysis. In this case, weights correspond to the similarity indexes among protein sequences, which can be used... more
This paper proposes a new method to identify communities in generally weighted complex networks and apply it to phylogenetic analysis. In this case, weights correspond to the similarity indexes among protein sequences, which can be
used for network construction so that the network structure can be analyzed to recover phylogenetically useful information
from its properties. The analyses discussed here are mainly based on the modular character of protein similarity networks,
explored through the Newman-Girvan algorithm, with the help of the neighborhood matrix Mˆ . The most relevant networks
are found when the network topology changes abruptly revealing distinct modules related to the sets of organisms to which the proteins belong. Sound biological information can be retrieved by the computational routines used in the network approach, without using biological assumptions other than those incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases, also some bacterial classes corresponded totally (100%) or to a great extent (.70%) to the modules. We checked for internal consistency in the obtained results, and we scored close to 84% of matches for community pertinence when comparisons between the results were performed. To illustrate how to use the network-based method, we employed data for enzymes involved in the chitin metabolic pathway that are present in more than 100
organisms from an original data set containing 1,695 organisms, downloaded from GenBank on May 19, 2007. A preliminary
comparison between the outcomes of the network-based method and the results of methods based on Bayesian, distance,
likelihood, and parsimony criteria suggests that the former is as reliable as these commonly used methods. We conclude
that the network-based method can be used as a powerful tool for retrieving modularity information from weighted networks, which is useful for phylogenetic analysis.
used for network construction so that the network structure can be analyzed to recover phylogenetically useful information
from its properties. The analyses discussed here are mainly based on the modular character of protein similarity networks,
explored through the Newman-Girvan algorithm, with the help of the neighborhood matrix Mˆ . The most relevant networks
are found when the network topology changes abruptly revealing distinct modules related to the sets of organisms to which the proteins belong. Sound biological information can be retrieved by the computational routines used in the network approach, without using biological assumptions other than those incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases, also some bacterial classes corresponded totally (100%) or to a great extent (.70%) to the modules. We checked for internal consistency in the obtained results, and we scored close to 84% of matches for community pertinence when comparisons between the results were performed. To illustrate how to use the network-based method, we employed data for enzymes involved in the chitin metabolic pathway that are present in more than 100
organisms from an original data set containing 1,695 organisms, downloaded from GenBank on May 19, 2007. A preliminary
comparison between the outcomes of the network-based method and the results of methods based on Bayesian, distance,
likelihood, and parsimony criteria suggests that the former is as reliable as these commonly used methods. We conclude
that the network-based method can be used as a powerful tool for retrieving modularity information from weighted networks, which is useful for phylogenetic analysis.