980 resultados para Computational Identification


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Background Flower development in kiwifruit (Actinidia spp.) is initiated in the first growing season, when undifferentiated primordia are established in latent shoot buds. These primordia can differentiate into flowers in the second growing season, after the winter dormancy period and upon accumulation of adequate winter chilling. Kiwifruit is an important horticultural crop, yet little is known about the molecular regulation of flower development. Results To study kiwifruit flower development, nine MADS-box genes were identified and functionally characterized. Protein sequence alignment, phenotypes obtained upon overexpression in Arabidopsis and expression patterns suggest that the identified genes are required for floral meristem and floral organ specification. Their role during budbreak and flower development was studied. A spontaneous kiwifruit mutant was utilized to correlate the extended expression domains of these flowering genes with abnormal floral development. Conclusions This study provides a description of flower development in kiwifruit at the molecular level. It has identified markers for flower development, and candidates for manipulation of kiwifruit growth, phase change and time of flowering. The expression in normal and aberrant flowers provided a model for kiwifruit flower development.

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Background The genetic regulation of flower color has been widely studied, notably as a character used by Mendel and his predecessors in the study of inheritance in pea. Methodology/Principal Findings We used the genome sequence of model legumes, together with their known synteny to the pea genome to identify candidate genes for the A and A2 loci in pea. We then used a combination of genetic mapping, fast neutron mutant analysis, allelic diversity, transcript quantification and transient expression complementation studies to confirm the identity of the candidates. Conclusions/Significance We have identified the pea genes A and A2. A is the factor determining anthocyanin pigmentation in pea that was used by Gregor Mendel 150 years ago in his study of inheritance. The A gene encodes a bHLH transcription factor. The white flowered mutant allele most likely used by Mendel is a simple G to A transition in a splice donor site that leads to a mis-spliced mRNA with a premature stop codon, and we have identified a second rare mutant allele. The A2 gene encodes a WD40 protein that is part of an evolutionarily conserved regulatory complex.

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Much of the diversity of anthocyanins is due to the action of glycosyltransferases, which add sugar moieties to anthocyanidins. We identified two glycosyltransferases, F3GT1 and F3GGT1, from red-fleshed kiwifruit (Actinidia chinensis) that perform sequential glycosylation steps. Red-fleshed genotypes of kiwifruit accumulate anthocyanins mainly in the form of cyanidin 3-O-xylo-galactoside. Genes in the anthocyanin and flavonoid biosynthetic pathway were identified and shown to be expressed in fruit tissue. However, only the expression of the glycosyltransferase F3GT1 was correlated with anthocyanin accumulation in red tissues. Recombinant enzyme assays in vitro and in vivo RNA interference (RNAi) demonstrated the role of F3GT1 in the production of cyanidin 3-O-galactoside. F3GGT1 was shown to further glycosylate the sugar moiety of the anthocyanins. This second glycosylation can affect the solubility and stability of the pigments and modify their colour. We show that recombinant F3GGT1 can catalyse the addition of UDP-xylose to cyanidin 3-galactoside. While F3GGT1 is responsible for the end-product of the pathway, F3GT1 is likely to be the key enzyme regulating the accumulation of anthocyanin in red-fleshed kiwifruit varieties.

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Background Transcription factors (TFs) co-ordinately regulate target genes that are dispersed throughout the genome. This co-ordinate regulation is achieved, in part, through the interaction of transcription factors with conserved cis-regulatory motifs that are in close proximity to the target genes. While much is known about the families of transcription factors that regulate gene expression in plants, there are few well characterised cis-regulatory motifs. In Arabidopsis, over-expression of the MYB transcription factor PAP1 (PRODUCTION OF ANTHOCYANIN PIGMENT 1) leads to transgenic plants with elevated anthocyanin levels due to the co-ordinated up-regulation of genes in the anthocyanin biosynthetic pathway. In addition to the anthocyanin biosynthetic genes, there are a number of un-associated genes that also change in expression level. This may be a direct or indirect consequence of the over-expression of PAP1. Results Oligo array analysis of PAP1 over-expression Arabidopsis plants identified genes co-ordinately up-regulated in response to the elevated expression of this transcription factor. Transient assays on the promoter regions of 33 of these up-regulated genes identified eight promoter fragments that were transactivated by PAP1. Bioinformatic analysis on these promoters revealed a common cis-regulatory motif that we showed is required for PAP1 dependent transactivation. Conclusion Co-ordinated gene regulation by individual transcription factors is a complex collection of both direct and indirect effects. Transient transactivation assays provide a rapid method to identify direct target genes from indirect target genes. Bioinformatic analysis of the promoters of these direct target genes is able to locate motifs that are common to this sub-set of promoters, which is impossible to identify with the larger set of direct and indirect target genes. While this type of analysis does not prove a direct interaction between protein and DNA, it does provide a tool to characterise cis-regulatory sequences that are necessary for transcription activation in a complex list of co-ordinately regulated genes.

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This study explored how the social context influences the stress-buffering effects of social support on employee adjustment. It was anticipated that the positive relationship between support from colleagues and employee adjustment would be more marked for those strongly identifying with their work team. Furthermore, as part of a three-way interactive effect, it was predicted that high identification would increase the efficacy of coworker support as a buffer of two role stressors (role overload and role ambiguity). One hundred and 55 employees recruited from first-year psychology courses enrolled at two Australian universities were surveyed. Hierarchical multiple regression analyses revealed that the negative main effect of role ambiguity on job satisfaction was significant for those employees with low levels of team identification, whereas high team identifiers were buffered from the deleterious effect of role ambiguity on job satisfaction. There also was a significant interaction between coworker support and team identification. The positive effect of coworker support on job satisfaction was significant for high team identifiers, whereas coworker support was not a source of satisfaction for those employees with low levels of team identification. A three-way interaction emerged among the focal variables in the prediction of psychological well-being, suggesting that the combined benefits of coworker support and team identification under conditions of high demand may be limited and are more likely to be observed when demands are low.

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Person re-identification is particularly challenging due to significant appearance changes across separate camera views. In order to re-identify people, a representative human signature should effectively handle differences in illumination, pose and camera parameters. While general appearance-based methods are modelled in Euclidean spaces, it has been argued that some applications in image and video analysis are better modelled via non-Euclidean manifold geometry. To this end, recent approaches represent images as covariance matrices, and interpret such matrices as points on Riemannian manifolds. As direct classification on such manifolds can be difficult, in this paper we propose to represent each manifold point as a vector of similarities to class representers, via a recently introduced form of Bregman matrix divergence known as the Stein divergence. This is followed by using a discriminative mapping of similarity vectors for final classification. The use of similarity vectors is in contrast to the traditional approach of embedding manifolds into tangent spaces, which can suffer from representing the manifold structure inaccurately. Comparative evaluations on benchmark ETHZ and iLIDS datasets for the person re-identification task show that the proposed approach obtains better performance than recent techniques such as Histogram Plus Epitome, Partial Least Squares, and Symmetry-Driven Accumulation of Local Features.

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The collision-induced dissociation ( CID) mass spectra of the \[M-H](-) anions of methyl, ethyl, and tert-butyl hydroperoxides have been measured over a range of collision energies in a flowing afterglow - selected ion flow tube (FA-SIFT) mass spectrometer. Activation of the CH3OO- anion is found to give predominantly HO- fragment anions whilst CH3CH2OO- and (CH3)(3)COO- produce HOO- as the major ionic fragment. These results, and other minor fragmentation pathways, can be rationalized in terms of unimolecular rearrangement of the activated anions with subsequent decomposition. The rearrangement reactions occur via initial abstraction of a proton from the alpha-carbon in the case of CH3OO- or the beta-carbon for CH3CH2OO- and (CH3)(3)COO-. Electronic structure calculations suggest that for the CH3CH2OO- anion, which can theoretically undergo both alpha- and beta-proton abstraction, the latter pathway, resulting in HOO- + CH2CH2, is energetically preferred.

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Hindered amine light stabilisers (HALS) are the most effective antioxidants currently available for polymer systems in post-production, in-service applications, yet the mechanism of their action is still not fully understood. Structural characterisation of HALS in polymer matrices, particularly the identification of structural modifications brought about by oxidative conditions, is critical to aid mechanistic understanding of the prophylactic effects of these molecules. In this work, electrospray ionisation tandem mass spectrometry (ESI-MS/MS) was applied to the analysis of a suite of commercially available 2,2,6,6-tetramethylpiperidine-based HALS. Fragmentation mechanisms for the \[M + H](+) ions are proposed, which provide a rationale for the product ions observed in the MS/MS and MS(3) mass spectra of N-H, N-CH(3), N-C(O)CH(3) and N-OR containing HALS (where R is an alkyl substituent). A common product ion at m/z 123 was identified for the group of antioxidants containing N-H, N-CH3 or N-C(0)CH3 functionality, and this product ion was employed in precursor ion scans on a triple quadrupole mass spectrometer to identify the HALS species present in a crude extract from of a polyester-based coil coating. Using MS/MS, two degradation products were unambiguously identified. This technique provides a simple and selective approach to monitoring HALS structures within complex matrices. Copyright (C) 2010 John Wiley & Sons, Ltd.

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Recent developments in mass spectrometry and chromatography provide new possibilities for the identification and in some instances quantification of a wide range of lipids in complex matrices. These advances in analytical technologies have provided a tantalizing glimpse of the true structural diversity of lipids in nature and have reinvigorated interest in the role of lipids in biology. While technological advances have been impressive, difficulties in the ready identification of sites of unsaturation (i.e., double bond position) within these molecules presents a significant impediment to understanding lipid biochemistry. This is of particular importance given the growing body of literature suggesting that the presence of naturally occurring lipid double bond isomers can have a significant influence, both positive and negative, on the development of pathologies such as cancer, cardiovascular disease and type 2 diabetes. This article provides a critical review of the Current suite of analytical approaches to the challenge of identification of the position of carbon-carbon double bonds in intact lipids. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

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The purpose of this study was to derive ActiGraph cut-points for sedentary (SED), light-intensity physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) in toddlers and evaluate their validity in an independent sample. The predictive validity of established preschool cut-points were also evaluated and compared. Twenty-two toddlers (mean age = 2.1 years ± 0.4 years) wore an ActiGraph accelerometer during a videotaped 20-min play period. Videos were subsequently coded for physical activity (PA) intensity using the modified Children's Activity Rating Scale (CARS). Receiver operating characteristic (ROC) curve analyses were conducted to determine cut-points. Predictive validity was assessed in an independent sample of 18 toddlers (mean age = 2.3 ± 0.4 years). From the ROC curve analyses, the 15-s count ranges corresponding to SED, LPA, and MVPA were 0–48, 49–418, and >418 counts/15 s, respectively. Classification accuracy was fair for the SED threshold (ROC-AUC = 0.74, 95% confidence interval = 0.71–0.76) and excellent for MVPA threshold (ROC-AUC = 0.90, 95% confidence interval = 0.88–0.92). In the cross-validation sample, the toddler cut-point and established preschool cut-points significantly overestimated time spent in SED and underestimated time in spent in LPA. For MVPA, mean differences between observed and predicted values for the toddler and Pate cut-points were not significantly different from zero. In summary, the ActiGraph accelerometer can provide useful group-level estimates of MVPA in toddlers. The results support the use of the Pate cut-point of 420 counts/15 s for MVPA.

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Most of existing motorway traffic safety studies using disaggregate traffic flow data aim at developing models for identifying real-time traffic risks by comparing pre-crash and non-crash conditions. One of serious shortcomings in those studies is that non-crash conditions are arbitrarily selected and hence, not representative, i.e. selected non-crash data might not be the right data comparable with pre-crash data; the non-crash/pre-crash ratio is arbitrarily decided and neglects the abundance of non-crash over pre-crash conditions; etc. Here, we present a methodology for developing a real-time MotorwaY Traffic Risk Identification Model (MyTRIM) using individual vehicle data, meteorological data, and crash data. Non-crash data are clustered into groups called traffic regimes. Thereafter, pre-crash data are classified into regimes to match with relevant non-crash data. Among totally eight traffic regimes obtained, four highly risky regimes were identified; three regime-based Risk Identification Models (RIM) with sufficient pre-crash data were developed. MyTRIM memorizes the latest risk evolution identified by RIM to predict near future risks. Traffic practitioners can decide MyTRIM’s memory size based on the trade-off between detection and false alarm rates. Decreasing the memory size from 5 to 1 precipitates the increase of detection rate from 65.0% to 100.0% and of false alarm rate from 0.21% to 3.68%. Moreover, critical factors in differentiating pre-crash and non-crash conditions are recognized and usable for developing preventive measures. MyTRIM can be used by practitioners in real-time as an independent tool to make online decision or integrated with existing traffic management systems.

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Two-photon fluorescence spectroscopy has been performed on rat skeletal muscles to investigate the effect of fixation processes on the micro-environments of the endogenous fluorophors in rat skeletal muscles. The two-photon fluorescence spectra measured for different fixation periods show a differential among those samples that were fixed in water, formalin and methanol, respectively. The results imply that two-photon fluorescence spectroscopy can be a potential technique for identification of healthy and malignant biological tissues.

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Data associated with germplasm collections are typically large and multivariate with a considerable number of descriptors measured on each of many accessions. Pattern analysis methods of clustering and ordination have been identified as techniques for statistically evaluating the available diversity in germplasm data. While used in many studies, the approaches have not dealt explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions). To consider the application of these techniques to germplasm evaluation data, 11328 accessions of groundnut (Arachis hypogaea L) from the International Research Institute for the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the rainy and post-rainy growing seasons were used. The ordination technique of principal component analysis was used to reduce the dimensionality of the germplasm data. The identification of phenotypically similar groups of accessions within large scale data via the computationally intensive hierarchical clustering techniques was not feasible and non-hierarchical techniques had to be used. Finite mixture models that maximise the likelihood of an accession belonging to a cluster were used to cluster the accessions in this collection. The patterns of response for the different growing seasons were found to be highly correlated. However, in relating the results to passport and other characterisation and evaluation descriptors, the observed patterns did not appear to be related to taxonomy or any other well known characteristics of groundnut.

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This thesis developed a new method for measuring extremely low amounts of organic and biological molecules, using Surface enhanced Raman Spectroscopy. This method has many potential applications, e.g. medical diagnosis, public health, food provenance, antidoping, forensics and homeland security. The method development used caffeine as the small molecule example, and erythropoietin (EPO) as the large molecule. This method is much more sensitive and specific than currently used methods; rapid, simple and cost effective. The method can be used to detect target molecules in beverages and biological fluids without the usual preparation steps.

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Molecular biology is a scientific discipline which has changed fundamentally in character over the past decade to rely on large scale datasets – public and locally generated - and their computational analysis and annotation. Undergraduate education of biologists must increasingly couple this domain context with a data-driven computational scientific method. Yet modern programming and scripting languages and rich computational environments such as R and MATLAB present significant barriers to those with limited exposure to computer science, and may require substantial tutorial assistance over an extended period if progress is to be made. In this paper we report our experience of undergraduate bioinformatics education using the familiar, ubiquitous spreadsheet environment of Microsoft Excel. We describe a configurable extension called QUT.Bio.Excel, a custom ribbon, supporting a rich set of data sources, external tools and interactive processing within the spreadsheet, and a range of problems to demonstrate its utility and success in addressing the needs of students over their studies.