Predição de promotores de Bacillus subtilis usando técnicas de aprendizado de máquina

One of the most important goals of bioinformatics is the ability to identify genes in uncharacterized DNA sequences on world wide database. Gene expression on prokaryotes initiates when the RNA-polymerase enzyme interacts with DNA regions called promoters. In these regions are located the main regulatory elements of the transcription process. Despite the improvement of in vitro techniques for molecular biology analysis, characterizing and identifying a great number of promoters on a genome is a complex task. Nevertheless, the main drawback is the absence of a large set of promoters to identify conserved patterns among the species. Hence, a in silico method to predict them on any species is a challenge. Improved promoter prediction methods can be one step towards developing more reliable ab initio gene prediction methods. In this work, we present an empirical comparison of Machine Learning (ML) techniques such as Na¨ýve Bayes, Decision Trees, Support Vector Machines and Neural Networks, Voted Perceptron, PART, k-NN and and ensemble approaches (Bagging and Boosting) to the task of predicting Bacillus subtilis. In order to do so, we first built two data set of promoter and nonpromoter sequences for B. subtilis and a hybrid one. In order to evaluate of ML methods a cross-validation procedure is applied. Good results were obtained with methods of ML like SVM and Naïve Bayes using B. subtilis. However, we have not reached good results on hybrid database

Não-extensividade em percolação por ligações de longo - alcance

A linear chain do not present phase transition at any finite temperature in a one dimensional system considering only first neighbors interaction. An example is the Ising ferromagnet in which his critical temperature lies at zero degree. Analogously, in percolation like disordered geometrical systems, the critical point is given by the critical probability equals to one. However, this situation can be drastically changed if we consider long-range bonds, replacing the probability distribution by a function like . In this kind of distribution the limit α → ∞ corresponds to the usual first neighbor bond case. In the other hand α = 0 corresponds to the well know "molecular field" situation. In this thesis we studied the behavior of Pc as a function of a to the bond percolation specially in d = 1. Our goal was to check a conjecture proposed by Tsallis in the context of his Generalized Statistics (a generalization to the Boltzmann-Gibbs statistics). By this conjecture, the scaling laws that depend with the size of the system N, vary in fact with the quantitie

Caracterização da geometria de depósitos sedimentares na borda sudoeste da Bacia`Potiguar

This study focuses on the potential of several techniques used to identify depositional geometries and paleogeographical investigation on the SW border of the Potiguar Basin. Three areas were selected for an integrated geological, geophysical and geochemistry study. The main used techniques were facies analysis, remote sensing,ground penetrating radar (GPR) and gamma-ray in outcrops, as well as petrographic microscope observations and the using of scanning eletronic microscopic (SEM), and Carbon and Oxygen Isotopic study in the carbonate tufa. These methodological approaches were very efficient in the facies analysis of 2D geometries. The GPR profiles carried out in Quixeré identified important geological reflectors which allowed to the identification of depositional geometries of tufa. However, GPR profiles were not able to identify geological reflectors in the Apodi and Olho d´Água da Bica outcrops. Gammaray profiles also presented good results, which justify their use in 1D and 2D geometric analysis. Carbon and Oxygen Isotopic analyses were also used to investigate paleoenvironmental setting of tufa deposits. It is important to remark the excellent resultsof GRP using in the identification of deposition al geometries of tufa and their contact relationships with the underlying rocks. Field analysis of faults indicate a vertical sigma-1 orientation which was associated to normal faults