996 resultados para Distance Matrix


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The statement that pairs of individuals from different populations are often more genetically similar than pairs from the same population is a widespread idea inside and outside the scientific community. Witherspoon et al. [""Genetic similarities within and between human populations,"" Genetics 176:351-359 (2007)] proposed an index called the dissimilarity fraction (omega) to access in a quantitative way the validity of this statement for genetic systems. Witherspoon demonstrated that, as the number of loci increases, omega decreases to a point where, when enough sampling is available, the statement is false. In this study, we applied the dissimilarity fraction to Howells`s craniometric database to establish whether or not similar results are obtained for cranial morphological traits. Although in genetic studies thousands of loci are available, Howells`s database provides no more than 55 metric traits, making the contribution of each variable important. To cope with this limitation, we developed a routine that takes this effect into consideration when calculating. omega Contrary to what was observed for the genetic data, our results show that cranial morphology asymptotically approaches a mean omega of 0.3 and therefore supports the initial statement-that is, that individuals from the same geographic region do not form clear and discrete clusters-further questioning the idea of the existence of discrete biological clusters in the human species. Finally, by assuming that cranial morphology is under an additive polygenetic model, we can say that the population history signal of human craniometric traits presents the same resolution as a neutral genetic system dependent on no more than 20 loci.

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The objective of this work was to study the effect of selective thinning on! the genetic divergence in progenies of Pinus caribaea var. bahamensis, aiming to identify the most productive and divergent progenies for the use of improvement program. The test of progenies containing 119 progenies and two commercial controls were planted in March 1990, using 11 x 11 square lattice design, sextuple, partially balanced, disposed in lineal plots with six trees in the spacing of 3,0 x 3,0m. 13 years after planting thinning was realized (selection for DBH), with 50% selection intensity based on Multi-effect index, leaving three trees per plot in all the experiment. The evaluations were done at four situations: A (before the thinning); B (thinned trees); C (remaining trees after thinning) and D (one year after thinning). The analyzed traits were: height, diameter at breast height (DBH), volume, form of stem and wood density. The genetic divergence among the progenies was studied with aid of the canonical variables and of clustering of Tocher method using the generalized distance matrix of Mahalanobis (D(2)) as estimate of the genetic similarity. The progenies were grouped in four groups in situation A, fourteen in the situation B, two in the situation C and three in the situation D. The selective thinning of the trees within of the progenies caused a change in the genetic divergence among the progenies, genetically homogenizing the progenies, as demonstrated by the generalized distances of Mahalanobis, clustering of Tocher' and canonical variables methods; The. thinning made possible a high uniformity in respect to the relative contribution, of the traits for the total genetic divergence. The techniques, of clustering were efficient to identify groups of divergent,progenies for the use hybridization and little divergent progenies for the use in backcross program.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The genus Arachis is endemic to South America and comprises 80 species, 69 of which have already been described and eleven not yet published. The genus includes the cultivated peanut ( A. hypogaea) and several forage species, the most important ones being A. glabrata and A. pintoi. Accessions of section Rhizomatosae, including three tetraploid species 2n = 4x = 40 (A. glabrata, A. pseudovillosa and A. nitida nom. nud.) and one diploid species 2n = 2x = 20 (A. burkartii), were evaluated using RAPD markers to assay genetic variability within and among species. The ten random primers used yielded a total of 113 polymorphic bands. The data were scored as the presence or absence of each band in each sample. A distance matrix and dendrogram were obtained using Link's coefficient and the neighbor-joining method. Most accessions analyzed grouped into two major clusters: the first comprised most accessions of A. glabrata and accessions of A. nitida, and the second cluster comprised accessions of A. burkartii. Arachis pseudovillosa and a few accessions of A. glabrata and A. nitida were placed between these major clusters. The diploid and tetraploid species were grouped quite separately, suggesting that the tetraploids did not originate from the diploid species analyzed.

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The objective of this work was to study the effect of selective thinning on the genetic divergence in progenies of Pinus caribaea var. bahamensis, aiming to identify the most productive and divergent progenies for the use of improvement program. The test of progenies containing 119 progenies and two commercial controls were planted in March 1990, using 11 × 11 square lattice design, sextuple, partially balanced, disposed in lineal plots with six trees in the spacing of 3,0 × 3,0m. 13 years after planting thinning was realized (selection for DBH), with 50% selection intensity based on Multi-effect index, leaving three trees per plot in all the experiment. The evaluations were done at four situations: A (before the thinning); B (thinned trees); C (remaining trees after thinning) and D (one year after thinning). The analyzed traits were: height, diameter at breast height (DBH), volume, form of stem and wood density. The genetic divergence among the progenies was studied with aid of the canonical variables and of clustering of Tocher method, using the generalized distance matrix of Mahalanobis (D2) as estimate of the genetic similarity. The progenies were grouped in four groups in situation A, fourteen in the situation B, two in the situation C and three in the situation D. The selective thinning of the trees within of the progenies caused a change in the genetic divergence among the progenies, genetically homogenizing the progenies, as demonstrated by the generalized distances of Mahalanobis, clustering of Tocher' and canonical variables methods. The thinning made possible a high uniformity in respect to the relative contribution of the traits for the total genetic divergence. The techniques of clustering were efficient to identify groups of divergent progenies for the use hybridization and little divergent progenies for the use in backcross program.

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In the present study, the coding region of the H gene was sequenced and analyzed in fourteen genera of New World primates (Alouatta, Aotus, Ateles, Brachyteles, Cacajao, Callicebus, Callithrix, Cebus, Chiropotes, Lagothrix, Leontopithecus, Pithecia, Saguinus, and Saimiri), in order to investigate the evolution of the gene. The analyses revealed that this coding region contains 1,101 nucleotides, with the exception of Brachyteles, the callitrichines (Callithrix, Leontopithecus, and Saguinus) and one species of Callicebus (moloch), in which one codon was deleted. In the primates studied, the high GC content (63%), the nonrandom distribution of codons and the low evolution rate of the gene (0.513 substitutions/site/MA in the order Primates) suggest the action of a purifying type of selective pressure, confirmed by the Z-test. Our analyses did not identify mutations equivalent to those responsible for the H-deficient phenotypes found in humans, nor any other alteration that might explain the lack of expression of the gene in the erythrocytes of Neotropical monkeys. The phylogenetic trees obtained for the H gene and the distance matrix data suggest the occurrence of divergent evolution in the primates.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Tuber borchii (Ascomycota, order Pezizales) is highly valued truffle sold in local markets in Italy. Despite its economic importance, knowledge on its distribution and population variation is scarce. The objective of this work was to investigate the evolutionary forces shaping the genetic structure of this fungus using coalescent and phylogenetic methods to reconstruct the evolutionary history of populations in Italy. To assess population structure, 61 specimens were collected from 11 different Provinces of Italy. Sampling was stratified across hosts and habitats to maximize coverage in native oak and pine stands and both mychorrizae and fruiting bodies were collected. Samples were identified considering anatomo-morphological characters. DNA was extracted and both multilocus (AFLP) and single-locus (18 loci from rDNA, nDNA, and mtDNA) approaches were used to look for polymorphisms. Screening AFLP profiles, both Jaccard and Dice coefficients of similarity were utilized to transform binary matrix into a distance matrix and then to desume Neighbour-Joining trees. Though these are only preliminary examinations, phylogenetic trees were totally concordant with those deriving from single locus analyses. Phylogenetic analyses of the nuclear loci were performed using maximum likelihood with PAUP and a combined phylogenetic inference, using Bayesian estimation with all nuclear gene regions, was carried out. To reconstruct the evolutionary history, we estimated recurrent migration, migration across the history of the sample, and estimated the mutation and approximate age of mutations in each tree using SNAP Workbench. The combined phylogenetic tree using Bayesian estimation suggests that there are two main haplotypes that are difficult to be differentiated on the basis of morphology, of ecological parameters and symbiontic tree. Between these two lineages, that occur in sympatry within T. borchii populations, there is no evidence of recurrent migration. However, migration over the history of the sample was asymmetrical suggesting that isolation was a result of interrupted gene flow followed by range expansion. Low levels of divergence between the haplotypes indicate that there are likely to be two cryptic species within the T. borchii population sampled. Our results suggest that isolation between populations of T. borchii could have led to reproductive isolation between two lineages. This isolation is likely due to sympatric speciation caused by a multiple colonization from different refugia or a recent isolation. In attempting to determinate whether these haplotypes represent separate species or a partition of the same species we applied Biological and Mechanistic species Concepts. Notwithstanding, further analyses are necessary to evaluate if selection favoured premating or post-mating isolation.

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To identify genetic susceptibility loci for severe diabetic retinopathy, 286 Mexican-Americans with type 2 diabetes from Starr County, Texas completed detailed physical and ophthalmologic examinations including fundus photography for diabetic retinopathy grading. 103 individuals with moderate-to-severe non-proliferative diabetic retinopathy or proliferative diabetic retinopathy were defined as cases for this study. DNA samples extracted from study subjects were genotyped using the Affymetrix GeneChip® Human Mapping 100K Set, which includes 116,204 single nucleotide polymorphisms (SNPs) across the whole genome. Single-marker allelic tests and 2- to 8-SNP sliding-window Haplotype Trend Regression implemented in HelixTreeTM were first performed with these direct genotypes to identify genes/regions contributing to the risk of severe diabetic retinopathy. An additional 1,885,781 HapMap Phase II SNPs were imputed from the direct genotypes to expand the genomic coverage for a more detailed exploration of genetic susceptibility to diabetic retinopathy. The average estimated allelic dosage and imputed genotypes with the highest posterior probabilities were subsequently analyzed for associations using logistic regression and Fisher's Exact allelic tests, respectively. To move beyond these SNP-based approaches, 104,572 directly genotyped and 333,375 well-imputed SNPs were used to construct genetic distance matrices based on 262 retinopathy candidate genes and their 112 related biological pathways. Multivariate distance matrix regression was then used to test hypotheses with genes and pathways as the units of inference in the context of susceptibility to diabetic retinopathy. This study provides a framework for genome-wide association analyses, and implicated several genes involved in the regulation of oxidative stress, inflammatory processes, histidine metabolism, and pancreatic cancer pathways associated with severe diabetic retinopathy. Many of these loci have not previously been implicated in either diabetic retinopathy or diabetes. In summary, CDC73, IL12RB2, and SULF1 had the best evidence as candidates to influence diabetic retinopathy, possibly through novel biological mechanisms related to VEGF-mediated signaling pathway or inflammatory processes. While this study uncovered some genes for diabetic retinopathy, a comprehensive picture of the genetic architecture of diabetic retinopathy has not yet been achieved. Once fully understood, the genetics and biology of diabetic retinopathy will contribute to better strategies for diagnosis, treatment and prevention of this disease.^

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The assessment of the reliability of systems which learn from data is a key issue to investigate thoroughly before the actual application of information processing techniques to real-world problems. Over the recent years Gaussian processes and Bayesian neural networks have come to the fore and in this thesis their generalisation capabilities are analysed from theoretical and empirical perspectives. Upper and lower bounds on the learning curve of Gaussian processes are investigated in order to estimate the amount of data required to guarantee a certain level of generalisation performance. In this thesis we analyse the effects on the bounds and the learning curve induced by the smoothness of stochastic processes described by four different covariance functions. We also explain the early, linearly-decreasing behaviour of the curves and we investigate the asymptotic behaviour of the upper bounds. The effect of the noise and the characteristic lengthscale of the stochastic process on the tightness of the bounds are also discussed. The analysis is supported by several numerical simulations. The generalisation error of a Gaussian process is affected by the dimension of the input vector and may be decreased by input-variable reduction techniques. In conventional approaches to Gaussian process regression, the positive definite matrix estimating the distance between input points is often taken diagonal. In this thesis we show that a general distance matrix is able to estimate the effective dimensionality of the regression problem as well as to discover the linear transformation from the manifest variables to the hidden-feature space, with a significant reduction of the input dimension. Numerical simulations confirm the significant superiority of the general distance matrix with respect to the diagonal one.In the thesis we also present an empirical investigation of the generalisation errors of neural networks trained by two Bayesian algorithms, the Markov Chain Monte Carlo method and the evidence framework; the neural networks have been trained on the task of labelling segmented outdoor images.

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Paper presented at Geo-Spatial Crossroad GI_Forum, Salzburg, Austria.

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Ultra low-load-dynamic microhardness testing facilitates the hardness measurements in a very low volume of the material and thus is suited for characterization of the interfaces in MMC's. This paper details the studies on age-hardening behavior of the interfaces in Al-Cu-5SiC(p) composites characterized using this technique. Results of hardness studies have been further substantiated by TEM observations. In the solution-treated condition, hardness is maximum at the particle/matrix interface and decreases with increasing distance from the interface. This could be attributed to the presence of maximum dislocation density at the interface which decreases with increasing distance from the interface. In the case of composites subjected to high temperature aging, hardening at the interface is found to be faster than the bulk matrix and the aging kinetics becomes progressively slower with increasing distance from the interface. This is attributed to the dislocation density gradient at the interface, leading to enhanced nucleation and growth of precipitates at the interface compared to the bulk matrix. TEM observations reveal that the sizes of the precipitates decrease with increasing distance from the interface and thus confirms the retardation in aging kinetics with increasing distance from the interface.

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Clustering techniques which can handle incomplete data have become increasingly important due to varied applications in marketing research, medical diagnosis and survey data analysis. Existing techniques cope up with missing values either by using data modification/imputation or by partial distance computation, often unreliable depending on the number of features available. In this paper, we propose a novel approach for clustering data with missing values, which performs the task by Symmetric Non-Negative Matrix Factorization (SNMF) of a complete pair-wise similarity matrix, computed from the given incomplete data. To accomplish this, we define a novel similarity measure based on Average Overlap similarity metric which can effectively handle missing values without modification of data. Further, the similarity measure is more reliable than partial distances and inherently possesses the properties required to perform SNMF. The experimental evaluation on real world datasets demonstrates that the proposed approach is efficient, scalable and shows significantly better performance compared to the existing techniques.

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By using six 4.5 Hz geophones, surface wave tests were performed on four different sites by dropping freely a 65 kg mass from a height of 5 m. The receivers were kept far away from the source to eliminate the arrival of body waves. Three different sources to nearest receiver distances (S), namely, 46 m, 56 m and 66 m, were chosen. Dispersion curves were drawn for all the sites. The maximum wavelength (lambda(max)), the maximum depth (d(max)) up to which exploration can be made and the frequency content of the signals depends on the site stiffness and the value of S. A stiffer site yields greater values of lambda(max) and d(max). For stiffer sites, an increase in S leads to an increase in lambda(max). The predominant time durations of the signals increase from stiffer to softer sites. An inverse analysis was also performed based on the stiffness matrix approach in conjunction with the maximum vertical flexibility coefficient of ground surface to establish the governing mode of excitation. For the Site 2, the results from the surface wave tests were found to compare reasonably well with that determined on the basis of cross boreholes seismic tests. (C) 2015 Elsevier Ltd. All rights reserved.