Prediction of protein-protein interface region based on structural information

Orientador: Clesio Luiz TozziTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia EletricaResumo: Este trabalho aborda o problema de predição de regiões de interface proteína-proteína, baseado em medidas de propriedades físico-químicas e estruturais. A abordagem considera os aminoácidos da superfície da proteína como as unidades básicas para classificação, o que elimina a restrição de uso de patches, considerada por preditores do mesmo tipo. Este preditor é complementado por um segundo preditor, que identifica, dentre os aminoácidos da interface, os mais relevantes do ponto de vista de energia de ligação proteína-proteína, conhecidos como hot spots. A abordagem apresentada permite a utilização dos classificadores de forma independente na predição dos aminoácidos de interface e dos hot spots. Diferente de outras abordagens encontradas na literatura para predição de hot spots, a abordagem empregada não depende do conhecimento da estrutura do complexo protéico e permite que a predição de hot spots seja realizada em complemento à predição dos aminoácidos da interface. O desempenho alcançado pelo preditor na identificação de hot spots é superior ao obtido por outros preditores descritos na literatura e que utilizam o mesmo conjunto de dados e critério de avaliação de desempenho.Abstract: This work approaches the problem of protein-proteins interface region prediction based on measures of physical-chemical and structural properties. The approach considers the amino acids of the protein surface as the basic units for classification, such that the restriction of use of patches, considered by similar predictors, is eliminated. This predictor is complemented by a second one, which identifies, among the interface amino acids, those which are most relevant from the standpoint of protein-protein binding energy. The classifiers can be used independently, for predicting interface amino acids and hot spots. Unlike other approaches for prediction of hot spots, described in the literature, the proposed approach does not depend on the knowledge of the protein structure in complex. This allows predicting hot spots in complement to the prediction of the interface amino acids. Concerning the identification of hot spots, the proposed predictor outperformed those, described in the literature, which use the same data set and criterion for performance evaluation.DoutoradoEngenharia de ComputaçãoDoutor em Engenharia Elétric

Prediction of binding hot spot residues by using structural and evolutionary parameters

In this work, we present a method for predicting hot spot residues by using a set of structural and evolutionary parameters. Unlike previous studies, we use a set of parameters which do not depend on the structure of the protein in complex, so that the predictor can also be used when the interface region is unknown. Despite the fact that no information concerning proteins in complex is used for prediction, the application of the method to a compiled dataset described in the literature achieved a performance of 60.4%, as measured by F-Measure, corresponding to a recall of 78.1% and a precision of 49.5%. This result is higher than those reported by previous studies using the same data set

Reconhecimento e localização de objetos bi-dimensionais parcialmente visiveis

Orientador: Marcio Luiz de Andrade NettoDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia EletricaResumo: Este trabalho refere-se aos problemas envolvidos na construção de um sistema capaz de reconhecer e localizar objetos bi-dimensionais parcialmente visíveis e dispostos de forma aleatória. Para isto, são consideradas as técnicas mais correntemente utilizadas para a construção de um sistema de visão computacional. Define-se um domínio de aplicação e, então, descreve-se a definição e implementação de um sistema capaz de realizar tal tarefa. Os resultados obtidos são apresentados e os problemas encontrados, discutidosMestradoMestre em Engenharia Elétric

Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach

Background: Meat quality involves many traits, such as marbling, tenderness, juiciness, and backfat thickness, all of which require attention from livestock producers. Backfat thickness improvement by means of traditional selection techniques in Canchim beef cattle has been challenging due to its low heritability, and it is measured late in an animal's life. Therefore, the implementation of new methodologies for identification of single nucleotide polymorphisms (SNPs) linked to backfat thickness are an important strategy for genetic improvement of carcass and meat quality.Results: The set of SNPs identified by the random forest approach explained as much as 50% of the deregressed estimated breeding value (dEBV) variance associated with backfat thickness, and a small set of 5 SNPs were able to explain 34% of the dEBV for backfat thickness. Several quantitative trait loci (QTL) for fat-related traits were found in the surrounding areas of the SNPs, as well as many genes with roles in lipid metabolism.Conclusions: These results provided a better understanding of the backfat deposition and regulation pathways, and can be considered a starting point for future implementation of a genomic selection program for backfat thickness in Canchim beef cattle. © 2013 Mokry et al.; licensee BioMed Central Ltd

Outcomes in Newly Diagnosed Atrial Fibrillation and History of Acute Coronary Syndromes: Insights from GARFIELD-AF

BACKGROUND: Many patients with atrial fibrillation have concomitant coronary artery disease with or without acute coronary syndromes and are in need of additional antithrombotic therapy. There are few data on the long-term clinical outcome of atrial fibrillation patients with a history of acute coronary syndrome. This is a 2-year study of atrial fibrillation patients with or without a history of acute coronary syndromes

Analysis of Outcomes in Ischemic vs Nonischemic Cardiomyopathy in Patients With Atrial Fibrillation A Report From the GARFIELD-AF Registry

IMPORTANCE Congestive heart failure (CHF) is commonly associated with nonvalvular atrial fibrillation (AF), and their combination may affect treatment strategies and outcomes