980 resultados para Computational Identification
Resumo:
The cossid moth (Coryphodema tristis) has a broad range of native tree hosts in South Africa. The moth recently moved into non-native Eucalyptus plantations in South Africa, on which it now causes significant damage. Here we investigate the chemicals involved in pheromone communication between the sexes of this moth in order to better understand its ecology, and with a view to potentially develop management tools for it. In particular, we characterize female gland extracts and headspace samples through coupled gas chromatography electro-antennographic detection (GC-EAD) and two dimensional gas chromatography mass spectrometry (GCxGC-MS). Tentative identities of the potential pheromone compounds were confirmed by comparing both retention time and mass spectra with authentic standards. Two electrophysiologically active pheromone compounds, tetradecyl acetate (14:OAc) and Z9-tetradecenyl acetate (Z9-14:OAc) were identified from pheromone gland extracts, and an additional compound (Z9-14:OH) from headspace samples. We further determined dose response curves for the identified compounds and six other structurally similar compounds that are common to the order Cossidae. Male antennae showed superior sensitivity toward Z9-14:OAc, Z7-tetradecenyl acetate (Z7-14:OAc), E9-tetradecenyl acetate (E9-14:OAc), Z9-tetradecenol (Z9-14:OH) and Z9-tetradecenal (Z9-14:Ald) when compared to female antennae. While we could show electrophysiological responses to single pheromone compounds, behavioral attraction of males was dependent on the synergistic effect of at least two of these compounds. Signal specificity is shown to be gained through pheromone blends. A field trial showed that a significant number of males were caught only in traps baited with a combination of Z9-14:OAc (circa 95 of the ratio) and Z9-14:OH. Addition of 14:OAc to this mixture also improved the number of males caught, although not significantly. This study represents a major step towards developing a useful attractant to be used in management tools for C. tristis and contributes to the understanding of chemical communication and biology of this group of insects.
Resumo:
Key message The potential for exploiting heterosis for sorghum hybrid production in Ethiopia with improved local adaptation and farmers preferences has been investigated and populations suitable for initial hybrid development have been identified. Abstract Hybrids in sorghum have demonstrated increased productivity and stability of performance in the developed world. In Ethiopia, the uptake of hybrid sorghum has been limited to date, primarily due to poor adaptation and absence of farmer’s preferred traits in existing hybrids. This study aimed to identify complementary parental pools to develop locally adapted hybrids, through an analysis of whole genome variability of 184 locally adapted genotypes and introduced hybrid parents (R and B). Genetic variability was assessed using genetic distance, model-based STRUCTURE analysis and pair-wise comparison of groups. We observed a high degree of genetic similarity between the Ethiopian improved inbred genotypes and a subset of landraces adapted to lowland agro-ecology with the introduced R lines. This coupled with the genetic differentiation from existing B lines, indicated that these locally adapted genotype groups are expected to have similar patterns of heterotic expression as observed between introduced R and B line pools. Additionally, the hybrids derived from these locally adapted genotypes will have the benefit of containing farmers preferred traits. The groups most divergent from introduced B lines were the Ethiopian landraces adapted to highland and intermediate agro-ecologies and a subset of lowland-adapted genotypes, indicating the potential for increased heterotic response of their hybrids. However, these groups were also differentiated from the R lines, and hence are different from the existing complementary heterotic pools. This suggests that although these groups could provide highly divergent parental pools, further research is required to investigate the extent of heterosis and their hybrid performance.
Resumo:
OBJECTIVES: 1. To determine whether incomplete rigor mortis resolution and 'cold shock' play a role in development of tough fish syndrome (TFS) in tropical Saddletail snapper. 2. To identify links between TFS and specific physiological factors in tropical Saddletail snapper. 3. Communicate findings and recommendations to stakeholders and assist with implementation of any changes to fishing or handling practices required.
Resumo:
Large-scale chromosome rearrangements such as copy number variants (CNVs) and inversions encompass a considerable proportion of the genetic variation between human individuals. In a number of cases, they have been closely linked with various inheritable diseases. Single-nucleotide polymorphisms (SNPs) are another large part of the genetic variance between individuals. They are also typically abundant and their measuring is straightforward and cheap. This thesis presents computational means of using SNPs to detect the presence of inversions and deletions, a particular variety of CNVs. Technically, the inversion-detection algorithm detects the suppressed recombination rate between inverted and non-inverted haplotype populations whereas the deletion-detection algorithm uses the EM-algorithm to estimate the haplotype frequencies of a window with and without a deletion haplotype. As a contribution to population biology, a coalescent simulator for simulating inversion polymorphisms has been developed. Coalescent simulation is a backward-in-time method of modelling population ancestry. Technically, the simulator also models multiple crossovers by using the Counting model as the chiasma interference model. Finally, this thesis includes an experimental section. The aforementioned methods were tested on synthetic data to evaluate their power and specificity. They were also applied to the HapMap Phase II and Phase III data sets, yielding a number of candidates for previously unknown inversions, deletions and also correctly detecting known such rearrangements.
Resumo:
Speeding is a major contributor to road injuries and fatalities and remains prevalent. Changing community perceptions about speeding is an important priority. Austroads commissioned research to identify a range of potential interventions for future trial and evaluation aimed at creating, increasing, and/or sustaining public demand for safer speeds. This project had three phases: a literature review; consultations with key stakeholders regarding intervention options (including feasibility, and likely benefits and costs of identified interventions); and providing research results, including recommendations for future phases of the program of work. The literature review led to the development of a draft Campaign Strategy targeting nine aims across three themes underpinning this research: 1) creating, 2) increasing, and 3) sustaining public demand for safer speeds on the road. Twenty-one stakeholders commented on the suitability and feasibility of, and likely barriers to, countermeasures within the draft Campaign Strategy and its applicability to the Australian and New Zealand context. There was overwhelming positive support for the proposed Campaign Strategy by the majority of respondents; many, noting that it addressed key misperceptions and complemented many existing approaches. A small number of respondents expressed some concerns with various aspects. Stakeholder feedback was incorporated into the final proposed Campaign Strategy to enhance its potential effectiveness. Wide diversity across jurisdictions makes the recommendation of individual interventions for specific areas problematic. Individual jurisdictions should consider a range of costs and benefits of the proposed Campaign Strategy to determine the likely feasibility from their unique perspective. Issues to be addressed when considering implementation of the proposed Campaign Strategy include speed limit setting policies, resourcing, messaging and advertising strategies, and political will associated with promoting safer speeds.
Resumo:
The specific activity of glutamine synthetase (L-glutamate: ammonia ligase, EC 6.3.1.2) in surface grown Aspergillus niger was increased 3-5 fold when grown on L-glutamate or potassium nitrate, compared to the activity obtained on ammonium chloride. The levels of glutamine synthetase was regulated by the availability of nitrogen source like NH4 + , and further, the enzyme is repressed by increasing concentrations of NH4 +. In contrast to other micro-organisms, the Aspergillus niger enzyme was neither specifically inactivated by NH4+ or L-glutamine nor regulated by covalent modification.Glutamine synthetase from Aspergillus niger was purified to homogenity. The native enzyme is octameric with a molecular weight of 385,000±25,000. The enzyme also catalyses Mn2+ or Mg2+-dependent synthetase and Mn2+-dependent transferase activity.Aspergillus niger glutamine synthetase was completely inactivated by two mol of phenylglyoxal and one mol of N-ethylmaleimide with second order rate constants of 3·8 M–1 min–1 and 760 M–1 min–1 respectively. Ligands like Mg. ATP, Mg. ADP, Mg. AMP, L-glutamate NH4+, Mn2+ protected the enzyme against inactivation. The pattern of inactivation and protection afforded by different ligands against N-ethylamaleimide and phenylglyoxal was remarkably similar. These results suggest that metal ATP complex acts as a substrate and interacts with an arginine ressidue at the active site. Further, the metal ion and the free nucleotide probably interact at other sites on the enzyme affecting the catalytic activity.
Resumo:
This thesis which consists of an introduction and four peer-reviewed original publications studies the problems of haplotype inference (haplotyping) and local alignment significance. The problems studied here belong to the broad area of bioinformatics and computational biology. The presented solutions are computationally fast and accurate, which makes them practical in high-throughput sequence data analysis. Haplotype inference is a computational problem where the goal is to estimate haplotypes from a sample of genotypes as accurately as possible. This problem is important as the direct measurement of haplotypes is difficult, whereas the genotypes are easier to quantify. Haplotypes are the key-players when studying for example the genetic causes of diseases. In this thesis, three methods are presented for the haplotype inference problem referred to as HaploParser, HIT, and BACH. HaploParser is based on a combinatorial mosaic model and hierarchical parsing that together mimic recombinations and point-mutations in a biologically plausible way. In this mosaic model, the current population is assumed to be evolved from a small founder population. Thus, the haplotypes of the current population are recombinations of the (implicit) founder haplotypes with some point--mutations. HIT (Haplotype Inference Technique) uses a hidden Markov model for haplotypes and efficient algorithms are presented to learn this model from genotype data. The model structure of HIT is analogous to the mosaic model of HaploParser with founder haplotypes. Therefore, it can be seen as a probabilistic model of recombinations and point-mutations. BACH (Bayesian Context-based Haplotyping) utilizes a context tree weighting algorithm to efficiently sum over all variable-length Markov chains to evaluate the posterior probability of a haplotype configuration. Algorithms are presented that find haplotype configurations with high posterior probability. BACH is the most accurate method presented in this thesis and has comparable performance to the best available software for haplotype inference. Local alignment significance is a computational problem where one is interested in whether the local similarities in two sequences are due to the fact that the sequences are related or just by chance. Similarity of sequences is measured by their best local alignment score and from that, a p-value is computed. This p-value is the probability of picking two sequences from the null model that have as good or better best local alignment score. Local alignment significance is used routinely for example in homology searches. In this thesis, a general framework is sketched that allows one to compute a tight upper bound for the p-value of a local pairwise alignment score. Unlike the previous methods, the presented framework is not affeced by so-called edge-effects and can handle gaps (deletions and insertions) without troublesome sampling and curve fitting.
Resumo:
Matrix decompositions, where a given matrix is represented as a product of two other matrices, are regularly used in data mining. Most matrix decompositions have their roots in linear algebra, but the needs of data mining are not always those of linear algebra. In data mining one needs to have results that are interpretable -- and what is considered interpretable in data mining can be very different to what is considered interpretable in linear algebra. --- The purpose of this thesis is to study matrix decompositions that directly address the issue of interpretability. An example is a decomposition of binary matrices where the factor matrices are assumed to be binary and the matrix multiplication is Boolean. The restriction to binary factor matrices increases interpretability -- factor matrices are of the same type as the original matrix -- and allows the use of Boolean matrix multiplication, which is often more intuitive than normal matrix multiplication with binary matrices. Also several other decomposition methods are described, and the computational complexity of computing them is studied together with the hardness of approximating the related optimization problems. Based on these studies, algorithms for constructing the decompositions are proposed. Constructing the decompositions turns out to be computationally hard, and the proposed algorithms are mostly based on various heuristics. Nevertheless, the algorithms are shown to be capable of finding good results in empirical experiments conducted with both synthetic and real-world data.
Resumo:
This thesis presents methods for locating and analyzing cis-regulatory DNA elements involved with the regulation of gene expression in multicellular organisms. The regulation of gene expression is carried out by the combined effort of several transcription factor proteins collectively binding the DNA on the cis-regulatory elements. Only sparse knowledge of the 'genetic code' of these elements exists today. An automatic tool for discovery of putative cis-regulatory elements could help their experimental analysis, which would result in a more detailed view of the cis-regulatory element structure and function. We have developed a computational model for the evolutionary conservation of cis-regulatory elements. The elements are modeled as evolutionarily conserved clusters of sequence-specific transcription factor binding sites. We give an efficient dynamic programming algorithm that locates the putative cis-regulatory elements and scores them according to the conservation model. A notable proportion of the high-scoring DNA sequences show transcriptional enhancer activity in transgenic mouse embryos. The conservation model includes four parameters whose optimal values are estimated with simulated annealing. With good parameter values the model discriminates well between the DNA sequences with evolutionarily conserved cis-regulatory elements and the DNA sequences that have evolved neutrally. In further inquiry, the set of highest scoring putative cis-regulatory elements were found to be sensitive to small variations in the parameter values. The statistical significance of the putative cis-regulatory elements is estimated with the Two Component Extreme Value Distribution. The p-values grade the conservation of the cis-regulatory elements above the neutral expectation. The parameter values for the distribution are estimated by simulating the neutral DNA evolution. The conservation of the transcription factor binding sites can be used in the upstream analysis of regulatory interactions. This approach may provide mechanistic insight to the transcription level data from, e.g., microarray experiments. Here we give a method to predict shared transcriptional regulators for a set of co-expressed genes. The EEL (Enhancer Element Locator) software implements the method for locating putative cis-regulatory elements. The software facilitates both interactive use and distributed batch processing. We have used it to analyze the non-coding regions around all human genes with respect to the orthologous regions in various other species including mouse. The data from these genome-wide analyzes is stored in a relational database which is used in the publicly available web services for upstream analysis and visualization of the putative cis-regulatory elements in the human genome.