Bayesian binary regression model: an application to in-hospital death after AMI prediction

Um modelo bayesiano de regressão binária é desenvolvido para predizer óbito hospitalar em pacientes acometidos por infarto agudo do miocárdio. Métodos de Monte Carlo via Cadeias de Markov (MCMC) são usados para fazer inferência e validação. Uma estratégia para construção de modelos, baseada no uso do fator de Bayes, é proposta e aspectos de validação são extensivamente discutidos neste artigo, incluindo a distribuição a posteriori para o índice de concordância e análise de resíduos. A determinação de fatores de risco, baseados em variáveis disponíveis na chegada do paciente ao hospital, é muito importante para a tomada de decisão sobre o curso do tratamento. O modelo identificado se revela fortemente confiável e acurado, com uma taxa de classificação correta de 88% e um índice de concordância de 83%.

Pattern recognition theory in nonlinear signal processing

A body of research has developed within the context of nonlinear signal and image processing that deals with the automatic, statistical design of digital window-based filters. Based on pairs of ideal and observed signals, a filter is designed in an effort to minimize the error between the ideal and filtered signals. The goodness of an optimal filter depends on the relation between the ideal and observed signals, but the goodness of a designed filter also depends on the amount of sample data from which it is designed. In order to lessen the design cost, a filter is often chosen from a given class of filters, thereby constraining the optimization and increasing the error of the optimal filter. To a great extent, the problem of filter design concerns striking the correct balance between the degree of constraint and the design cost. From a different perspective and in a different context, the problem of constraint versus sample size has been a major focus of study within the theory of pattern recognition. This paper discusses the design problem for nonlinear signal processing, shows how the issue naturally transitions into pattern recognition, and then provides a review of salient related pattern-recognition theory. In particular, it discusses classification rules, constrained classification, the Vapnik-Chervonenkis theory, and implications of that theory for morphological classifiers and neural networks. The paper closes by discussing some design approaches developed for nonlinear signal processing, and how the nature of these naturally lead to a decomposition of the error of a designed filter into a sum of the following components: the Bayes error of the unconstrained optimal filter, the cost of constraint, the cost of reducing complexity by compressing the original signal distribution, the design cost, and the contribution of prior knowledge to a decrease in the error. The main purpose of the paper is to present fundamental principles of pattern recognition theory within the framework of active research in nonlinear signal processing.

A Bayesian approach for assessing the stability of genotypes

Several statistical models can be used for assessing genotype X environment interaction (GEI) and studying genotypic stability. The objectives of this research were to show how (i) to use Bayesian methodology for computing Shukla's phenotypic stability variance and (ii) to incorporate prior information on the parameters for better estimation. Potato [Solanum tuberosum subsp. andigenum (Juz. & Bukasov) Hawkes], wheat (Triticum aestivum L.), and maize (Zea mays L.) multi environment trials (MET) were used for illustrating the application of the Bayes paradigm. The potato trial included 15 genotypes, but prior information for just three genotypes was used. The wheat trial used prior information on all 10 genotypes included in the trial, whereas for the maize trial, noninformative priors for the nine genotypes was used. Concerning the posterior distribution of the genotypic means, the maize MET with 20 sites gave less disperse posterior distributions of the genotypic means than did the posterior distribution of the genotypic means of the other METs, which included fewer environments. The Bayesian approach allows use of other statistical strategies such as the normal truncated distribution (used in this study). When analyzing grain yield, a lower bound of zero and an upper bound set by the researcher's experience can be used. The Bayesian paradigm offers plant breeders the possibility of computing the probability of a genotype being the best performer. The results of this study show that although some genotypes may have a very low probability of being the best in all sites, they have a relatively good chance of being among the five highest yielding genotypes.

Development of an open case-based decision-support system for diagnosis in oral pathology

Making diagnoses in oral pathology are often difficult and confusing in dental practice, especially for the lessexperienced dental student. One of the most promising areas in bioinformatics is computer-aided diagnosis, where a computer system is capable of imitating human reasoning ability and provides diagnoses with an accuracy approaching that of expert professionals. This type of system could be an alternative tool for assisting dental students to overcome the difficulties of the oral pathology learning process. This could allow students to define variables and information, important to improving the decision-making performance. However, no current open data management system has been integrated with an artificial intelligence system in a user-friendly environment. Such a system could also be used as an education tool to help students perform diagnoses. The aim of the present study was to develop and test an open case-based decisionsupport system.Methods: An open decision-support system based on Bayes' theorem connected to a relational database was developed using the C++ programming language. The software was tested in the computerisation of a surgical pathology service and in simulating the diagnosis of 43 known cases of oral bone disease. The simulation was performed after the system was initially filled with data from 401 cases of oral bone disease.Results: the system allowed the authors to construct and to manage a pathology database, and to simulate diagnoses using the variables from the database.Conclusion: Combining a relational database and an open decision-support system in the same user-friendly environment proved effective in simulating diagnoses based on information from an updated database.

A Bayesian Analysis of Spectral ARMA Model

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A Bayesian approach for constructing genetic maps when markers are miscoded

The advent of molecular markers has created opportunities for a better understanding of quantitative inheritance and for developing novel strategies for genetic improvement of agricultural species, using information on quantitative trait loci (QTL). A QTL analysis relies on accurate genetic marker maps. At present, most statistical methods used for map construction ignore the fact that molecular data may be read with error. Often, however, there is ambiguity about some marker genotypes. A Bayesian MCMC approach for inferences about a genetic marker map when random miscoding of genotypes occurs is presented, and simulated and real data sets are analyzed. The results suggest that unless there is strong reason to believe that genotypes are ascertained without error, the proposed approach provides more reliable inference on the genetic map.

A Bayesian approach to estimate the accuracy of in-house ELISA assay to measure rabies antibodies from compulsory vaccinated dogs and cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Solving the Levins' paradox in the logistic model to the population growth

We introduce a new method to improve Markov maps by means of a Bayesian approach. The method starts from an initial map model, wherefrom a likelihood function is defined which is regulated by a temperature-like parameter. Then, the new constraints are added by the use of Bayes rule in the prior distribution. We applied the method to the logistic map of population growth of a single species. We show that the population size is limited for all ranges of parameters, allowing thus to overcome difficulties in interpretation of the concept of carrying capacity known as the Levins paradox. © Published under licence by IOP Publishing Ltd.

Molecular phylogenetic relationships and phenotypic diversity in miniaturized toadlets, genus Brachycephalus (Amphibia: Anura: Brachycephalidae)

Toadlets of the genus Brachycephalus are endemic to the Atlantic rainforests of southeastern and southern Brazil. The 14 species currently described have snout-vent lengths less than 18. mm and are thought to have evolved through miniaturization: an evolutionary process leading to an extremely small adult body size. Here, we present the first comprehensive phylogenetic analysis for Brachycephalus, using a multilocus approach based on two nuclear (Rag-1 and Tyr) and three mitochondrial (Cyt b, 12S, and 16S rRNA) gene regions. Phylogenetic relationships were inferred using a partitioned Bayesian analysis of concatenated sequences and the hierarchical Bayesian method (BEST) that estimates species trees based on the multispecies coalescent model. Individual gene trees showed conflict and also varied in resolution. With the exception of the mitochondrial gene tree, no gene tree was completely resolved. The concatenated gene tree was completely resolved and is identical in topology and degree of statistical support to the individual mtDNA gene tree. On the other hand, the BEST species tree showed reduced significant node support relative to the concatenate tree and recovered a basal trichotomy, although some bipartitions were significantly supported at the tips of the species tree. Comparison of the log likelihoods for the concatenated and BEST trees suggests that the method implemented in BEST explains the multilocus data for Brachycephalus better than the Bayesian analysis of concatenated data. Landmark-based geometric morphometrics revealed marked variation in cranial shape between the species of Brachycephalus. In addition, a statistically significant association was demonstrated between variation in cranial shape and genetic distances estimated from the mtDNA and nuclear loci. Notably, B. ephippium and B. garbeana that are predicted to be sister-species in the individual and concatenated gene trees and the BEST species tree share an evolutionary novelty, the hyperossified dorsal plate. © 2011 Elsevier Inc.

A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes

A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes is introduced. The proposed model may accommodate the original single shift setting to the more realistic situation of gradual quality deterioration and allows the incorporation of an expert's opinion on the production process. Based on the number of inspections to be carried out until a defective item is found, the Bayesian operation for the distribution function that represents the increasing sequence of defective fractions during a cycle considering a mixture of Dirichlet processes as prior distribution is performed. Bayes estimates for relevant quantities are also obtained. © 2012 Elsevier B.V.

Automatic landslide recognition through Optimum-Path Forest

In this paper we shed light over the problem of landslide automatic recognition using supervised classification, and we also introduced the OPF classifier in this context. We employed two images acquired from Geoeye-MS satellite at March-2010 in the northwest (high steep areas) and north sides (pipeline area) covering the area of Duque de Caxias city, Rio de Janeiro State, Brazil. The landslide recognition rate has been assessed through a cross-validation with 10 runnings. In regard to the classifiers, we have used OPF against SVM with Radial Basis Function for kernel mapping and a Bayesian classifier. We can conclude that OPF, Bayes and SVM achieved high recognition rates, being OPF the fastest approach. © 2012 IEEE.

Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle

Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and Bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. © 2013 American Dairy Science Association.

Analysis of genetic correlations of hip height with selection indices and mature weight in Nelore cattle

Body size is directly related to the productive and reproductive performance of beef cattle raised under free-range conditions. In an attempt to better plan selection criteria, avoiding extremes in body size, this study estimated the heritabilities and genetic correlations of yearling hip height (YH) and mature hip height (MH) with selection indices obtained at weaning (WI) and yearling (YI) and mature weight (MW). Data from 102,373 Nelore animals born between 1984 and 2010, which belong to 263 farms that participate in genetic evaluation programmes of beef cattle conducted in Brazil and Paraguay, were used. The (co)variance components and genetic parameters were estimated by Bayesian inference in multi-trait analysis using an animal model. The mean heritabilities for YH, MH and MW were 0. 56 ± 0. 06, 0. 47 ± 0. 02 and 0. 42 ± 0. 02, respectively. The genetic correlation of YH with WI (0. 13 ± 0. 01) and YI (0. 11 ± 0. 01) was practically zero, whereas a higher correlation was observed with MW (0. 22 ± 0. 03). Positive genetic correlations of medium magnitude were estimated between MH and WI and YI (0. 23 ± 0. 01 and 0. 43 ± 0. 02, respectively). On the other hand, a high genetic correlation (0. 68 ± 0. 03) was observed between the indicator traits of mature body size (MH and MW). Considering the top 20 % of sire (896 sires) in terms of breeding values for the yearling index, the rank sire correlations between breeding values for MH and MW was 0. 62. In general, the results indicate that selection based on WI and YI should not lead to important changes in YH. However, an undesired correlated response in mature cow height is expected, particularly when selection is performed using YI. Therefore, changes in the body structure of Nelore females can be obtained when MH and MW is used as a selection criterion for cows. © 2012 Institute of Plant Genetics, Polish Academy of Sciences, Poznan.

Comparative cytogenetic analysis of some species of the Dendropsophus microcephalus group (Anura, Hylidae) in the light of phylogenetic inferences

Background: Dendropsophus is a monophyletic anuran genus with a diploid number of 30 chromosomes as an important synapomorphy. However, the internal phylogenetic relationships of this genus are poorly understood. Interestingly, an intriguing interspecific variation in the telocentric chromosome number has been useful in species identification. To address certain uncertainties related to one of the species groups of Dendropsophus, the D. microcephalus group, we carried out a cytogenetic analysis combined with phylogenetic inferences based on mitochondrial sequences, which aimed to aid in the analysis of chromosomal characters. Populations of Dendropsophus nanus, Dendropsophus walfordi, Dendropsophus sanborni, Dendropsophus jimi and Dendropsophus elianeae, ranging from the extreme south to the north of Brazil, were cytogenetically compared. A mitochondrial region of the ribosomal 12S gene from these populations, as well as from 30 other species of Dendropsophus, was used for the phylogenetic inferences. Phylogenetic relationships were inferred using maximum parsimony and Bayesian analyses.Results: The species D. nanus and D. walfordi exhibited identical karyotypes (2n = 30; FN = 52), with four pairs of telocentric chromosomes and a NOR located on metacentric chromosome pair 13. In all of the phylogenetic hypotheses, the paraphyly of D. nanus and D. walfordi was inferred. D. sanborni from Botucatu-SP and Torres-RS showed the same karyotype as D. jimi, with 5 pairs of telocentric chromosomes (2n = 30; FN = 50) and a terminal NOR in the long arm of the telocentric chromosome pair 12. Despite their karyotypic similarity, these species were not found to compose a monophyletic group. Finally, the phylogenetic and cytogenetic analyses did not cluster the specimens of D. elianeae according to their geographical occurrence or recognized morphotypes.Conclusions: We suggest that a taxonomic revision of the taxa D. nanus and D. walfordi is quite necessary. We also observe that the number of telocentric chromosomes is useful to distinguish among valid species in some cases, although it is unchanged in species that are not necessarily closely related phylogenetically. Therefore, inferences based on this chromosomal character must be made with caution; a proper evolutionary analysis of the karyotypic variation in Dendropsophus depends on further characterization of the telocentric chromosomes found in this group. © 2013 Medeiros et al.; licensee BioMed Central Ltd.

Microsatellite marker-based assessment of the biodiversity of native bioethanol yeast strains

Although many Brazilian sugar mills initiate the fermentation process by inoculating selected commercial Saccharomyces cerevisiae strains, the unsterile conditions of the industrial sugar cane ethanol fermentation process permit the constant entry of native yeast strains. Certain of those native strains are better adapted and tend to predominate over the initial strain, which may cause problems during fermentation. In the industrial fermentation process, yeast cells are often exposed to stressful environmental conditions, including prolonged cell recycling, ethanol toxicity and osmotic, oxidative or temperature stress. Little is known about these S. cerevisiae strains, although recent studies have demonstrated that heterogeneous genome architecture is exhibited by some selected well-adapted Brazilian indigenous yeast strains that display high performance in bioethanol fermentation. In this study, 11 microsatellite markers were used to assess the genetic diversity and population structure of the native autochthonous S. cerevisiae strains in various Brazilian sugar mills. The resulting multilocus data were used to build a similarity-based phenetic tree and to perform a Bayesian population structure analysis. The tree revealed the presence of great genetic diversity among the strains, which were arranged according to the place of origin and the collection year. The population structure analysis revealed genotypic differences among populations; in certain populations, these genotypic differences are combined to yield notably genotypically diverse individuals. The high yeast diversity observed among native S. cerevisiae strains provides new insights on the use of autochthonous high-fitness strains with industrial characteristics as starter cultures at bioethanol plants. © 2013 John Wiley & Sons, Ltd.