Plataforma de ensino e pesquisa para área médica /

Orientador: Bonald Cavalcante de FigueiredoCo-orientador: Helio PedriniTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências da Saúde, Programa de Pós-Graduação em Saúde da Criança e do Adolescente. Defesa: Curitiba, 2007Inclui bibliografiaÁrea de concentração : Informática em saúd

Princípios para a construção de banco de dados de imagens médicas

Orientador: Marcos Sfair SunyeDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Exata

Sistema de conferencia chat e audio para a área médica

Orientadora:Jeroniza Nunes MarchaukoskiMonografia (graduaçao) - Universidade Federal do Paraná, Escola Técnica, Curso de Graduaçao em Tecnologia em InformáticaInclui bibliografi

Sistema de conferencia chat e audio para a área médica

Orientadora:Jeroniza Nunes MarchaukoskiMonografia (graduaçao) - Universidade Federal do Paraná, Escola Técnica, Curso de Graduaçao em Tecnologia em InformáticaInclui bibliografi

Revista digital

Orientador: Jeroniza Nunes MarchaukoskiMonografia (graduação) - Universidade Federal do Paraná, Escola Técnica, Curso de Tecnologia em InformáticaInclui bibliografi

Comparative Analysis of Genomic Island Prediction Tools

Tools for genomic island prediction use strategies for genomic comparison analysis and sequence composition analysis. The goal of comparative analysis is to identify unique regions in the genomes of related organisms, whereas sequence composition analysis evaluates and relates the composition of specific regions with other regions in the genome. The goal of this study was to qualitatively and quantitatively evaluate extant genomic island predictors. We chose tools reported to produce significant results using sequence composition prediction, comparative genomics, and hybrid genomics methods. To maintain diversity, the tools were applied to eight complete genomes of organisms with distinct characteristics and belonging to different families. Escherichia coli CFT073 was used as a control and considered as the gold standard because its islands were previously curated in vitro. The results of predictions with the gold standard were manually curated, and the content and characteristics of each predicted island were analyzed. For other organisms, we created GenBank (GBK) files using Artemis software for each predicted island. We copied only the amino acid sequences from the coding sequence and constructed a multi-FASTA file for each predictor. We used BLASTp to compare all results and generate hits to evaluate similarities and differences among the predictions. Comparison of the results with the gold standard revealed that GIPSy produced the best results, covering ~91% of the composition and regions of the islands, followed by Alien Hunter (81%), IslandViewer (47.8%), Predict Bias (31%), GI Hunter (17%), and Zisland Explorer (16%). The tools with the best results in the analyzes of the set of organisms were the same ones that presented better performance in the tests with the gold standard

Software de apoio a projetos

Orientador: Jeroniza Nunes MarchaukoskiCo-orientador: Mauro José BelliMonografia (graduação) - Universidade Federal do Paraná, Escola Técnica, Curso de Tecnologia em InformáticaInclui bibliografi

Plataforma de ensino e pesquisa para área médica /

Orientador: Bonald Cavalcante de FigueiredoCo-orientador: Helio PedriniTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências da Saúde, Programa de Pós-Graduação em Saúde da Criança e do Adolescente. Defesa: Curitiba, 2007Inclui bibliografiaÁrea de concentração : Informática em saúd

New Tools in Orthology Analysis: A Brief Review of Promising Perspectives

Nowadays defying homology relationships among sequences is essential for biological research. Within homology the analysis of orthologs sequences is of great importance for computational biology, annotation of genomes and for phylogenetic inference. Since 2007, with the increase in the number of new sequences being deposited in large biological databases, researchers have begun to analyse computerized methodologies and tools aimed at selecting the most promising ones in the prediction of orthologous groups. Literature in this field of research describes the problems that the majority of available tools show, such as those encountered in accuracy, time required for analysis (especially in light of the increasing volume of data being submitted, which require faster techniques) and the automatization of the process without requiring manual intervention. Conducting our search through BMC, Google Scholar, NCBI PubMed, and Expasy, we examined more than 600 articles pursuing the most recent techniques and tools developed to solve most the problems still existing in orthology detection. We listed the main computational tools created and developed between 2011 and 2017, taking into consideration the differences in the type of orthology analysis, outlining the main features of each tool and pointing to the problems that each one tries to address. We also observed that several tools still use as their main algorithm the BLAST “all-against-all” methodology, which entails some limitations, such as limited number of queries, computational cost, and high processing time to complete the analysis. However, new promising tools are being developed, like OrthoVenn (which uses the Venn diagram to show the relationship of ortholog groups generated by its algorithm); or proteinOrtho (which improves the accuracy of ortholog groups); or ReMark (tackling the integration of the pipeline to turn the entry process automatic); or OrthAgogue (using algorithms developed to minimize processing time); and proteinOrtho (developed for dealing with large amounts of biological data). We made a comparison among the main features of four tool and tested them using four for prokaryotic genomas. We hope that our review can be useful for researchers and will help them in selecting the most appropriate tool for their work in the field of orthology