895 resultados para COMPLEX SEGREGATION ANALYSIS
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Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes.
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The goal of this study was to analyze the mode of inheritance of an overweight body condition in an experimental cat population. The cat population consisted of 95 cats of which 81 cats could be clearly classified into lean or overweight using the body condition scoring system according to Laflamme. The lean or overweight classification was then used for segregation analyses. Complex segregation analyses were employed to test for the significance of one environmental and 4 genetic models (general, mixed inheritance, major gene, and polygene). The general genetic model fit the data significantly better than the environmental model (P = 0.0013). Among all other models employed, the major gene model explained the segregation of the overweight phenotype best. This is the first study in which a genetic component could be shown to be responsible for the development of overweight in cats.
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We present the first comprehensive study, to our knowledge, on genomic chromosomal analysis in syndromic craniosynostosis. In total, 45 patients with craniosynostotic disorders were screened with a variety of methods including conventional karyotype, microsatellite segregation analysis, subtelomeric multiplex ligation-dependent probe amplification) and whole-genome array-based comparative genome hybridisation. Causative abnormalities were present in 42.2% (19/45) of the samples, and 27.8% (10/36) of the patients with normal conventional karyotype carried submicroscopic imbalances. Our results include a wide variety of imbalances and point to novel chromosomal regions associated with craniosynostosis. The high incidence of pure duplications or trisomies suggests that these are important mechanisms in craniosynostosis, particularly in cases involving the metopic suture.
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Using restriction fragment length polymorphism (RFLP) we have analyzed the segregation of alleles of the different vitellogenin genes of Xenopus laevis. The results demonstrate that the four genes whose expression is controlled by oestrogen, form two linkage groups. The genes A1, A2 and B1 are linked genetically whereas the fourth gene, the gene B2, segregates independently. The possible origin of this unexpected arrangement is discussed.
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Complex networks have been increasingly used in text analysis, including in connection with natural language processing tools, as important text features appear to be captured by the topology and dynamics of the networks. Following previous works that apply complex networks concepts to text quality measurement, summary evaluation, and author characterization, we now focus on machine translation (MT). In this paper we assess the possible representation of texts as complex networks to evaluate cross-linguistic issues inherent in manual and machine translation. We show that different quality translations generated by NIT tools can be distinguished from their manual counterparts by means of metrics such as in-(ID) and out-degrees (OD), clustering coefficient (CC), and shortest paths (SP). For instance, we demonstrate that the average OD in networks of automatic translations consistently exceeds the values obtained for manual ones, and that the CC values of source texts are not preserved for manual translations, but are for good automatic translations. This probably reflects the text rearrangements humans perform during manual translation. We envisage that such findings could lead to better NIT tools and automatic evaluation metrics.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In this paper, natural frequencies were analyzed (axial, torsional and flexural) and frequency response of a vertical rotor with a hard disk at the edge through the classical modal and complex analysis. The equation that rules the movement was obtained through the Lagrangian formulation. The model considered the effects of bending, torsion and axial deformation of the shaft, besides the gravitational and gyroscopic effects. The finite element method was used to discretize the structure into hollow cylindrical elements with 12 degrees of freedom. Mass, stiffness and gyroscopic matrices were explained consistently. The classical modal analysis, usually applied to stationary structures, does not consider an important characteristic of rotating machinery which are the methods of forward and backward whirl. Initially, through the traditional modal analysis, axial and torsional natural frequencies were obtained in a static shaft, since they do not suffer the influence of gyroscopic effects. Later research was performed by complex modal analysis. This type of tool, based on the use of complex coordinates to describe the dynamic behavior of rotating shaft, allows the decomposition of the system in two submodes, backward and forward. Thus, it is possible to clearly visualize that the orbit and direction of the precessional motion around the line of the rotating shaft is not deformed. A finite element program was developed using MATLAB (TM) and numerical simulations were performed to validate this model. Natural frequencies and directional frequency forced response (dFRF) were obtained using the complex modal analysis for a simple vertical rotor and also for a typical drill string used in the construction of oil wells.
Resumo:
Natural frequencies were analyzed (axial, torsional and flexural) and frequency response of a vertical rotor with a hard disk at the edge through the classical and complex modal analysis. The mathematical modeling was based on the theory of Euler-Bernoulli beam. The equation that rules the movement was obtained through the Lagrangian formulation. The model considered the effects of bending, torsion and axial deformation of the shaft, besides the gravitational and gyroscopic effects. The finite element method was used to discretize the structure into hollow cylindrical elements with 12 degrees of freedom. Mass, stiffness and gyroscopic matrices were explained consistently. This type of tool, based on the use of complex coordinates to describe the dynamic behavior of rotating shaft, allows the decomposition of the system in two submodes, backward and forward. Thus, it is possible to clearly visualize that the orbit and direction of the precessional motion around the line of the rotating shaft is not deformed. A finite element program was developed using Matlab ®, and numerical simulations were performed to validate this model.
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Methods from statistical physics, such as those involving complex networks, have been increasingly used in the quantitative analysis of linguistic phenomena. In this paper, we represented pieces of text with different levels of simplification in co-occurrence networks and found that topological regularity correlated negatively with textual complexity. Furthermore, in less complex texts the distance between concepts, represented as nodes, tended to decrease. The complex networks metrics were treated with multivariate pattern recognition techniques, which allowed us to distinguish between original texts and their simplified versions. For each original text, two simplified versions were generated manually with increasing number of simplification operations. As expected, distinction was easier for the strongly simplified versions, where the most relevant metrics were node strength, shortest paths and diversity. Also, the discrimination of complex texts was improved with higher hierarchical network metrics, thus pointing to the usefulness of considering wider contexts around the concepts. Though the accuracy rate in the distinction was not as high as in methods using deep linguistic knowledge, the complex network approach is still useful for a rapid screening of texts whenever assessing complexity is essential to guarantee accessibility to readers with limited reading ability. Copyright (c) EPLA, 2012
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Thesis (Ph.D.)--University of Washington, 2016-06
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Mandibular prognathism typically shows familial aggregation. Various genetic models have been described and it is assumed to be a multifactorial and polygenic trait, with a threshold for expression. Our goal was to examine specific genetic models of the familial transmission of this trait. The study sample comprised of 2,562 individuals from 55 families. Complete family histories for each proband were ascertained and the affection status of relatives were confirmed by lateral cephalograms, photographs, and dental models. Pedigrees were drawn using PELICAN and complex segregation analysis was performed using POINTER. Parts of some pedigrees were excluded to create one founder pedigrees, so the total N was 2,050. Analysis showed more affected females than males (P = 0.030). The majority of the pedigrees suggest autosomal dominant inheritance. Incomplete penetrance was demonstrated by the ratio of affected/unaffected parents and siblings. The heritability of mandibular prognathism was estimated to be 0.316. We conclude that there is a major gene that influences the expression of mandibular prognathism with clear signs of Mendelian inheritance and a multifactorial component. (C) 2007 Wiley-Liss, Inc.
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To test the hypothesis of a heritable base of ectopic ureters (EU) in Entlebucher Mountain Dogs (EMD) and to elucidate associated risk factors and mode of inheritance of the disease, 565 EMD were clinically investigated and population genetic analyses performed. Based on the location of the most caudal termination of the ureteral openings, 552 EMD were classified into three phenotype groups trigone, intravesically and extravesically ectopic based on results of abdominal sonography, urethra-cystoscopy and/or contrast-enhanced computed tomography. One-third (32.9%) of the phenotyped animals had normal terminations of both ureters in the bladder trigone, 47.3% had at least one intravesicular ectopic termination and 19.8% had at least one extravesicular ectopic termination. Multivariate mixed logistic regression revealed gender as a risk factor associated with EU as males were more often affected than females. Complex segregation analysis indicated a hereditary basis for EU in EMD and the involvement of a major gene in the occurrence of the extravesicular EU phenotype.