Identificação de genes MUTM em BACs da cana-de-açucar e caracterização preliminar destes genes e seus promotores

Sugarcane has an importance in Brazil due to sugar and biofuel production. Considering this aspect, there is basic research being done in order to understand its physiology to improve production. The aim of this research is the Base Excision Repair pathway, in special the enzyme MUTM DNA-glycosylase (formamidopyrimidine) which recognizes oxidized guanine in DNA. The sugarcane scMUTM genes were analyzed using four BACs (Bacterial Artificial Chromosome) from a sugarcane genomic library from R570 cultivar. The resulted showed the presence in the region that had homology to scMUTM the presence of transposable elements. Comparing the similarity, it was observed a highest similarity to Sorghum bicolor sequence, both nucleotide and peptide sequences. Furthermore, promoter regions from MUTM genes in some grass showed different cis-regulatory elements, among which, most were related to oxidative stress, suggesting a gene regulation by oxidative stress

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

Identificação de genes MUTM em BACs da cana-de-açucar e caracterização preliminar destes genes e seus promotores

Sugarcane has an importance in Brazil due to sugar and biofuel production. Considering this aspect, there is basic research being done in order to understand its physiology to improve production. The aim of this research is the Base Excision Repair pathway, in special the enzyme MUTM DNA-glycosylase (formamidopyrimidine) which recognizes oxidized guanine in DNA. The sugarcane scMUTM genes were analyzed using four BACs (Bacterial Artificial Chromosome) from a sugarcane genomic library from R570 cultivar. The resulted showed the presence in the region that had homology to scMUTM the presence of transposable elements. Comparing the similarity, it was observed a highest similarity to Sorghum bicolor sequence, both nucleotide and peptide sequences. Furthermore, promoter regions from MUTM genes in some grass showed different cis-regulatory elements, among which, most were related to oxidative stress, suggesting a gene regulation by oxidative stress