59 resultados para basis sets


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Both the rhino mouse and hairless mouse resulted from hairless gene mutation, but they show different phenotypes of skin physiology. The rhino mouse has more similar histological characters to human papular alopecia. Therefore rhino mouse is a good experimental animal model for human papular alopecia. This study reports a hairless mouse named rhino KIZ, arose from KM colony in Kunming Institue of Zoology, by systematic studies on morphology, skin histopathology, gene sequence, pedigree and protein domain analysis. The results demonstrate that a C-to-T transition in exon 11 of hr gene (The mutant gene has been applied for a Chinese patent (patent No. 03135280)) results in the rhino KIZ. The rhino KIZ with clear genetic mechanism will be a useful animal model.

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We built 64 sets of 3D models of DNA triplex base triplets (TBT) and minimized their energies. The TBTs were divided into 32 pairs of conjugated ones on the basis of their sequence characteristic, and the energies of each pair of them were compared and analyzed, the results showed: (i) The duplex DNA of which any strand contains at least a couple of A or T, has a preference for selecting the oligodeoxyribonucleic acid (ODN) strand containing abundant T to form TBT. (ii) The duplex DNA of which any strand contains at least a couple of G or C has a preference for selecting ODN containing abundant G to form symmetric antiparallel TBT, but selecting ODN containing abundant C to form asymmetric parallel TBT. (iii) The duplex DNA of which any strand contains only one of A, T, G or C has a preference for selecting ODN containing abundant pyrimidines (T or C) to form antiparallel TBT. Additionally, two examples of TBTs applications, in designing ODN to form triplex with duplex were presented. The energy calculation result revealed that 15-TCG is the best ligand of the HIV PPT duplex. The comparative analysis of energies of the conjugated TBTs provides directive significance for designing ODN strand that is easy to form triplex in theory. (C) 2002 Elsevier Science B.V. All rights reserved.

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A radial basis function neural network was employed to model the abundance of cyanobacteria. The trained network could predict the populations of two bloom forming algal taxa with high accuracy, Nostocales spp. and Anabaena spp., in the River Darling, Australia. To elucidate the population dynamics for both Nostocales spp. and Anabaena spp., sensitivity analysis was performed with the following results. Total Kjeldahl nitrogen had a very strong influence on the abundance of the two algal taxa, electrical conductivity had a very strong negative relationship with the population of the two algal species, and flow was identified as one dominant factor influencing algal blooms after a scatter plot revealed that high flow could significantly reduce the algal biomass for both Nostocales spp. and Anabaena spp. Other variables such as turbidity, color, and pH were less important in determining the abundance and succession of the algal blooms.

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No detailed food web research on macroinvertebrate community of lacustrine ecosystem was reported in China. The present study is the first attempt on the subject in Lake Biandantang, a macrophytic lake in Hubei Province. Food webs of the macroinvertebrate community were compiled bimonthly from March, 2002 to March, 2003. Dietary information was obtained from gut analysis. Linkage strength was quantified by combining estimates of energy flow (secondary production) with data of gut analysis. The macroinvertebrate community of Lake Biandantang was based heavily on detritus. Quantitative food webs showed the total ingestion ranged from 6930 to 36,340 mg dry mass m(-2) bimonthly. The ingestion of macroinvertebrate community was higher in the months with optimum temperature than that in other periods with higher or lower temperature. Through comparison, many patterns in benthic food web of Lake Biandantang are consistent with other detritus-based webs, such as stream webs, but different greatly from those based on autochthonous primary production (e.g. pelagic systems). It suggests that the trophic basis of the web is essential in shaping food web structure.

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Transferrin (TF) polymorphism was investigated in a color variety of goldfish (Carassius auratus), and its molecular basis analyzed. Three TF variants (A(1), A(2) and B-1) were identified from an inbred strain of the goldfish, of which A(1) and B-1 displayed a large electrophoretic difference on both native and SDS-PAGE gels. The TF cDNAs corresponding to variants A(1) and B-1 were cloned and sequenced from A(1)A(1), A(1)B(1) and B1B1 individuals, and their deduced amino acid sequences were analyzed. Substantial amino acid variation occurred between variants A(1) and B-1, with significant differences in peptide length, theoretical molecular weight (Mw) and isoelectric point (pI). No potential glycosylation sites were observed in the two amino acid sequences, which excluded the possibility that carbohydrate difference might cause electrophoretic variation among the TF variants. Further analysis suggested that the distinct electrophoretic mobility of the two variants A(1) and B-1 by SDS-PAGE resulted from their Mw difference, while the difference by the native PAGE could be explained by their pI variation. Furthermore, genomic DNA fragments containing the transferrin alleles were amplified and subjected to RFLP analysis in A(1)A(1), A(1)B(1) and B1B1 individuals. The data revealed characteristic banding patterns for each TF genotype, and demonstrated that the TF alleles A(1) and B-1 could be used as a co-dominant marker system. The initial work relating to the goldfish TF variants will benefit the understanding of the evolutionary and functional significance of TF polymorphism in fish.

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For a class of nonlinear dynamical systems, the adaptive controllers are investigated using direction basis function (DBF) in this paper. Based on the criterion of Lyapunov' stability, DBF is designed which guarantees that the output of the controlled system asymptotically tracks the reference signals. Finally, the simulation shows the good tracking effectiveness of the adaptive controller.

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Automatic molecular classification of cancer based on DNA microarray has many advantages over conventional classification based on morphological appearance of the tumor. Using artificial neural networks is a general approach for automatic classification. In this paper, Direction-Basis-Function neuron and Priority-Ordered algorithm are applied to neural networks. And the leukemia gene expression dataset is used as an example to testify the classifier. The result of our method is compared to that of SVM. It shows that our method makes a better performance than SVM.

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Basis path testing is a very powerful structural testing criterion. The number of test paths equals to the cyclomatic complexity of program defined by McCabe. Traditional test generation methods select the paths either without consideration of the constraints of variables or interactively. In this note, an efficient method is presented to generate a set of feasible basis paths. The experiments show that this method can generate feasible basis paths for real-world C programs automatically in acceptable time.