344 resultados para genetic manipulation


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In cloud computing, resource allocation and scheduling of multiple composite web services is an important and challenging problem. This is especially so in a hybrid cloud where there may be some low-cost resources available from private clouds and some high-cost resources from public clouds. Meeting this challenge involves two classical computational problems: one is assigning resources to each of the tasks in the composite web services; the other is scheduling the allocated resources when each resource may be used by multiple tasks at different points of time. In addition, Quality-of-Service (QoS) issues, such as execution time and running costs, must be considered in the resource allocation and scheduling problem. Here we present a Cooperative Coevolutionary Genetic Algorithm (CCGA) to solve the deadline-constrained resource allocation and scheduling problem for multiple composite web services. Experimental results show that our CCGA is both efficient and scalable.

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This chapter focuses on the interactions and roles between delays and intrinsic noise effects within cellular pathways and regulatory networks. We address these aspects by focusing on genetic regulatory networks that share a common network motif, namely the negative feedback loop, leading to oscillatory gene expression and protein levels. In this context, we discuss computational simulation algorithms for addressing the interplay of delays and noise within the signaling pathways based on biological data. We address implementational issues associated with efficiency and robustness. In a molecular biology setting we present two case studies of temporal models for the Hes1 gene (Monk, 2003; Hirata et al., 2002), known to act as a molecular clock, and the Her1/Her7 regulatory system controlling the periodic somite segmentation in vertebrate embryos (Giudicelli and Lewis, 2004; Horikawa et al., 2006).

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We introduce a genetic programming (GP) approach for evolving genetic networks that demonstrate desired dynamics when simulated as a discrete stochastic process. Our representation of genetic networks is based on a biochemical reaction model including key elements such as transcription, translation and post-translational modifications. The stochastic, reaction-based GP system is similar but not identical with algorithmic chemistries. We evolved genetic networks with noisy oscillatory dynamics. The results show the practicality of evolving particular dynamics in gene regulatory networks when modelled with intrinsic noise.

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The Giant Long-Armed Prawn, Macrobrachium lar is a freshwater species native to the Indo-Pacific. M. lar has a long-lived, passive, pelagic marine larval stage where larvae need to colonise freshwater within three months to complete their development. Dispersal is likely to be influenced by the extensive distances larvae must transit between small oceanic islands to find suitable freshwater habitat, and by prevailing east to west wind and ocean currents in the southern Pacific Ocean. Thus, both intrinsic and extrinsic factors are likely to influence wild population structure in this species. The present study sought to define the contemporary broad and fine-scale population genetic structure of Macrobrachium lar in the south-western Pacific Ocean. Three polymorphic microsatellite loci were used to assess patterns of genetic variation within and among 19 wild adult sample sites. Statistical procedures that partition variation implied that at both spatial scales, essentially all variation was present within sample sites and differentiation among sites was low. Any differentiation observed also was not correlated with geographical distance. Statistical approaches that measure genetic distance, at the broad-scale, showed that all south-western Pacific Islands were essentially homogeneous, with the exception of a well supported divergent Cook Islands group. These findings are likely the result of some combination of factors that may include the potential for allelic homoplasy, through to the effects of sampling regime. Based on the findings, there is most likely a divergent M. lar Cook Islands clade in the south-western Pacific Ocean, resulting from prevailing ocean currents. Confirmation of this pattern will require a more detailed analysis of nDNA variation using a larger number of loci and, where possible, use of larger population sizes.

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In this paper we construct a mathematical model for the genetic regulatory network of the lactose operon. This mathematical model contains transcription and translation of the lactose permease (LacY) and a reporter gene GFP. The probability of transcription of LacY is determined by 14 binding states out of all 50 possible binding states of the lactose operon based on the quasi-steady-state assumption for the binding reactions, while we calculate the probability of transcription for the reporter gene GFP based on 5 binding states out of 19 possible binding states because the binding site O2 is missing for this reporter gene. We have tested different mechanisms for the transport of thio-methylgalactoside (TMG) and the effect of different Hill coefficients on the simulated LacY expression levels. Using this mathematical model we have realized one of the experimental results with different LacY concentrations, which are induced by different concentrations of TMG.

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Recent studies have shown that small genetic regulatory networks (GRNs) can be evolved in silico displaying certain dynamics in the underlying mathematical model. It is expected that evolutionary approaches can help to gain a better understanding of biological design principles and assist in the engineering of genetic networks. To take the stochastic nature of GRNs into account, our evolutionary approach models GRNs as biochemical reaction networks based on simple enzyme kinetics and simulates them by using Gillespie’s stochastic simulation algorithm (SSA). We have already demonstrated the relevance of considering intrinsic stochasticity by evolving GRNs that show oscillatory dynamics in the SSA but not in the ODE regime. Here, we present and discuss first results in the evolution of GRNs performing as stochastic switches.

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Web service technology is increasingly being used to build various e-Applications, in domains such as e-Business and e-Science. Characteristic benefits of web service technology are its inter-operability, decoupling and just-in-time integration. Using web service technology, an e-Application can be implemented by web service composition — by composing existing individual web services in accordance with the business process of the application. This means the application is provided to customers in the form of a value-added composite web service. An important and challenging issue of web service composition, is how to meet Quality-of-Service (QoS) requirements. This includes customer focused elements such as response time, price, throughput and reliability as well as how to best provide QoS results for the composites. This in turn best fulfils customers’ expectations and achieves their satisfaction. Fulfilling these QoS requirements or addressing the QoS-aware web service composition problem is the focus of this project. From a computational point of view, QoS-aware web service composition can be transformed into diverse optimisation problems. These problems are characterised as complex, large-scale, highly constrained and multi-objective problems. We therefore use genetic algorithms (GAs) to address QoS-based service composition problems. More precisely, this study addresses three important subproblems of QoS-aware web service composition; QoS-based web service selection for a composite web service accommodating constraints on inter-service dependence and conflict, QoS-based resource allocation and scheduling for multiple composite services on hybrid clouds, and performance-driven composite service partitioning for decentralised execution. Based on operations research theory, we model the three problems as a constrained optimisation problem, a resource allocation and scheduling problem, and a graph partitioning problem, respectively. Then, we present novel GAs to address these problems. We also conduct experiments to evaluate the performance of the new GAs. Finally, verification experiments are performed to show the correctness of the GAs. The major outcomes from the first problem are three novel GAs: a penaltybased GA, a min-conflict hill-climbing repairing GA, and a hybrid GA. These GAs adopt different constraint handling strategies to handle constraints on interservice dependence and conflict. This is an important factor that has been largely ignored by existing algorithms that might lead to the generation of infeasible composite services. Experimental results demonstrate the effectiveness of our GAs for handling the QoS-based web service selection problem with constraints on inter-service dependence and conflict, as well as their better scalability than the existing integer programming-based method for large scale web service selection problems. The major outcomes from the second problem has resulted in two GAs; a random-key GA and a cooperative coevolutionary GA (CCGA). Experiments demonstrate the good scalability of the two algorithms. In particular, the CCGA scales well as the number of composite services involved in a problem increases, while no other algorithms demonstrate this ability. The findings from the third problem result in a novel GA for composite service partitioning for decentralised execution. Compared with existing heuristic algorithms, the new GA is more suitable for a large-scale composite web service program partitioning problems. In addition, the GA outperforms existing heuristic algorithms, generating a better deployment topology for a composite web service for decentralised execution. These effective and scalable GAs can be integrated into QoS-based management tools to facilitate the delivery of feasible, reliable and high quality composite web services.

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In this paper a new graph-theory and improved genetic algorithm based practical method is employed to solve the optimal sectionalizer switch placement problem. The proposed method determines the best locations of sectionalizer switching devices in distribution networks considering the effects of presence of distributed generation (DG) in fitness functions and other optimization constraints, providing the maximum number of costumers to be supplied by distributed generation sources in islanded distribution systems after possible faults. The proposed method is simulated and tested on several distribution test systems in both cases of with DG and non DG situations. The results of the simulations validate the proposed method for switch placement of the distribution network in the presence of distributed generation.

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Sutchi catfish (Pangasianodon hypophthalmus) – known more universally by the Vietnamese name ‘Tra’ is an economically important freshwater fish in the Mekong Delta in Vietnam that constitutes an important food resource. Artificial propagation technology for Tra catfish has only recently been developed along the main branches of the Mekong River where more than 60% of the local human population participate in fishing or aquaculture. Extensive support for catfish culture in general, and that of Tra (P. hypophthalmus) in particular, has been provided by the Vietnamese government to increase both the scale of production and to develop international export markets. In 2006, total Vietnamese catfish exports reached approximately 286,602 metric tons (MT) and were valued at 736.87 $M with a number of large new export destinations being developed. Total value of production from catfish culture has been predicted to increase to approximately USD 1 billion by 2020. While freshwater catfish culture in Vietnam has a promising future, concerns have been raised about long-term quality of fry and the effectiveness of current brood stock management practices, issues that have been largely neglected to date. In this study, four DNA markers (microsatellite loci: CB4, CB7, CB12 and CB13) that were developed specifically for Tra (P. hypophthalmus) in an earlier study were applied to examine the genetic quality of artificially propagated Tra fry in the Mekong Delta in Vietnam. The goals of the study were to assess: (i) how well available levels of genetic variation in Tra brood stock used for artificial propagation in the Mekong Delta of Vietnam (breeders from three private hatcheries and Research Institute of Aquaculture No2 (RIA2) founders) has been conserved; and (ii) whether or not genetic diversity had declined significantly over time in a stock improvement program for Tra catfish at RIA2. A secondary issue addressed was how genetic markers could best be used to assist industry development. DNA was extracted from fins of catfish collected from the two main branches of the Mekong River inf Vietnam, three private hatcheries and samples from the Tra improvement program at RIA2. Study outcomes: i) Genetic diversity estimates for Tra brood stock samples were similar to, and slightly higher than, wild reference samples. In addition, the relative contribution by breeders to fry in commercial private hatcheries strongly suggest that the true Ne is likely to be significantly less than the breeder numbers used; ii) in a stock improvement program for Tra catfish at RIA2, no significant differences were detected in gene frequencies among generations (FST=0.021, P=0.036>0.002 after Bonferroni correction); and only small differences were observed in alleles frequencies among sample populations. To date, genetic markers have not been applied in the Tra catfish industry, but in the current project they were used to evaluate the levels of genetic variation in the Tra catfish selective breeding program at RIA2 and to undertake genetic correlations between genetic marker and trait variation. While no associations were detected using only four loci, they analysis provided training in the practical applications of the use of molecular markers in aquaculture in general, and in Tra culture, in particular.

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Twin studies offer the opportunity to determine the relative contribution of genes versus environment in traits of interest. Here, we investigate the extent to which variance in brain structure is reduced in monozygous twins with identical genetic make-up. We investigate whether using twins as compared to a control population reduces variability in a number of common magnetic resonance (MR) structural measures, and we investigate the location of areas under major genetic influences. This is fundamental to understanding the benefit of using twins in studies where structure is the phenotype of interest. Twenty-three pairs of healthy MZ twins were compared to matched control pairs. Volume, T2 and diffusion MR imaging were performed as well as spectroscopy (MRS). Images were compared using (i) global measures of standard deviation and effect size, (ii) voxel-based analysis of similarity and (iii) intra-pair correlation. Global measures indicated a consistent increase in structural similarity in twins. The voxel-based and correlation analyses indicated a widespread pattern of increased similarity in twin pairs, particularly in frontal and temporal regions. The areas of increased similarity were most widespread for the diffusion trace and least widespread for T2. MRS showed consistent reduction in metabolite variation that was significant in the temporal lobe N-acetylaspartate (NAA). This study has shown the distribution and magnitude of reduced variability in brain volume, diffusion, T2 and metabolites in twins. The data suggest that evaluation of twins discordant for disease is indeed a valid way to attribute genetic or environmental influences to observed abnormalities in patients since evidence is provided for the underlying assumption of decreased variability in twins.

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Background: Known risk factors for secondary lymphedema only partially explain who develops lymphedema following cancer, suggesting that inherited genetic susceptibility may influence risk. Moreover, identification of molecular signatures could facilitate lymphedema risk prediction prior to surgery or lead to effective drug therapies for prevention or treatment. Recent advances in the molecular biology underlying development of the lymphatic system and related congenital disorders implicate a number of potential candidate genes to explore in relation to secondary lymphedema. Methods and Results: We undertook a nested case-control study, with participants who had developed lymphedema after surgical intervention within the first 18 months of their breast cancer diagnosis serving as cases (n=22) and those without lymphedema serving as controls (n=98), identified from a prospective, population-based, cohort study in Queensland, Australia. TagSNPs that covered all known genetic variation in the genes SOX18, VEGFC, VEGFD, VEGFR2, VEGFR3, RORC, FOXC2, LYVE1, ADM and PROX1 were selected for genotyping. Multiple SNPs within three receptor genes, VEGFR2, VEGFR3 and RORC, were associated with lymphedema defined by statistical significance (p<0.05) or extreme risk estimates (OR<0.5 or >2.0). Conclusions: These provocative, albeit preliminary, findings regarding possible genetic predisposition to secondary lymphedema following breast cancer treatment warrant further attention for potential replication using larger datasets.

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Vitamin A deficiency (VAD) is a serious problem in developing countries, affecting approximately 127 million children of preschool age and 7.2 million pregnant women each year. However, this deficiency is readily treated and prevented through adequate nutrition. This can potentially be achieved through genetically engineered biofortification of staple food crops to enhance provitamin A (pVA) carotenoid content. Bananas are the fourth most important food crop with an annual production of 100 million tonnes and are widely consumed in areas affected by VAD. However, the fruit pVA content of most widely consumed banana cultivars is low (~ 0.2 to 0.5 ìg/g dry weight). This includes cultivars such as the East African highland banana (EAHB), the staple crop in countries such as Uganda, where annual banana consumption is approximately 250 kg per person. This fact, in addition to the agronomic properties of staple banana cultivars such as vegetative reproduction and continuous cropping, make bananas an ideal target for pVA enhancement through genetic engineering. Interestingly, there are banana varieties known with high fruit pVA content (up to 27.8 ìg/g dry weight), although they are not widely consumed due to factors such as cultural preference and availability. The genes involved in carotenoid accumulation during banana fruit ripening have not been well studied and an understanding of the molecular basis for the differential capacity of bananas to accumulate carotenoids may impact on the effective production of genetically engineered high pVA bananas. The production of phytoene by the enzyme phytoene synthase (PSY) has been shown to be an important rate limiting determinant of pVA accumulation in crop systems such as maize and rice. Manipulation of this gene in rice has been used successfully to produce Golden Rice, which exhibits higher seed endosperm pVA levels than wild type plants. Therefore, it was hypothesised that differences between high and low pVA accumulating bananas could be due either to differences in PSY enzyme activity or factors regulating the expression of the psy gene. Therefore, the aim of this thesis was to investigate the role of PSY in accumulation of pVA in banana fruit of representative high (Asupina) and low (Cavendish) pVA banana cultivars by comparing the nucleic acid and encoded amino acid sequences of the banana psy genes, in vivo enzyme activity of PSY in rice callus and expression of PSY through analysis of promoter activity and mRNA levels. Initially, partial sequences of the psy coding region from five banana cultivars were obtained using reverse transcriptase (RT)-PCR with degenerate primers designed to conserved amino acids in the coding region of available psy sequences from other plants. Based on phylogenetic analysis and comparison to maize psy sequences, it was found that in banana, psy occurs as a gene family of at least three members (psy1, psy2a and psy2b). Subsequent analysis of the complete coding regions of these genes from Asupina and Cavendish suggested that they were all capable of producing functional proteins due to high conservation in the catalytic domain. However, inability to obtain the complete mRNA sequences of Cavendish psy2a, and isolation of two non-functional Cavendish psy2a coding region variants, suggested that psy2a expression may be impaired in Cavendish. Sequence analysis indicated that these Cavendish psy2a coding region variants may have resulted from alternate splicing. Evidence of alternate splicing was also observed in one Asupina psy1 coding region variant, which was predicted to produce a functional PSY1 isoform. The complete mRNA sequence of the psy2b coding regions could not be isolated from either cultivar. Interestingly, psy1 was cloned predominantly from leaf while psy2 was obtained preferentially from fruit, suggesting some level of tissue-specific expression. The Asupina and Cavendish psy1 and psy2a coding regions were subsequently expressed in rice callus and the activity of the enzymes compared in vivo through visual observation and quantitative measurement of carotenoid accumulation. The maize B73 psy1 coding region was included as a positive control. After several weeks on selection, regenerating calli showed a range of colours from white to dark orange representing various levels of carotenoid accumulation. These results confirmed that the banana psy coding regions were all capable of producing functional enzymes. No statistically significant differences in levels of activity were observed between banana PSYs, suggesting that differences in PSY activity were not responsible for differences in the fruit pVA content of Asupina and Cavendish. The psy1 and psy2a promoter sequences were isolated from Asupina and Cavendish gDNA using a PCR-based genome walking strategy. Interestingly, three Cavendish psy2a promoter clones of different sizes, representing possible allelic variants, were identified while only single promoter sequences were obtained for the other Asupina and Cavendish psy genes. Bioinformatic analysis of these sequences identified motifs that were previously characterised in the Arabidopsis psy promoter. Notably, an ATCTA motif associated with basal expression in Arabidopsis was identified in all promoters with the exception of two of the Cavendish psy2a promoter clones (Cpsy2apr2 and Cpsy2apr3). G1 and G2 motifs, linked to light-regulated responses in Arabidopsis, appeared to be differentially distributed between psy1 and psy2a promoters. In the untranscribed regulatory regions, the G1 motifs were found only in psy1 promoters, while the G2 motifs were found only in psy2a. Interestingly, both ATCTA and G2 motifs were identified in the 5’ UTRs of Asupina and Cavendish psy1. Consistent with other monocot promoters, introns were present in the Asupina and Cavendish psy1 5’ UTRs, while none were observed in the psy2a 5’ UTRs. Promoters were cloned into expression constructs, driving the â-glucuronidase (GUS) reporter gene. Transient expression of the Asupina and Cavendish psy1 and psy2a promoters in both Cavendish embryogenic cells and Cavendish fruit demonstrated that all promoters were active, except Cpsy2apr2 and Cpsy2apr3. The functional Cavendish psy2a promoter (Cpsy2apr1) appeared to have activity similar to the Asupina psy2a promoter. The activities of the Asupina and Cavendish psy1 promoters were similar to each other, and comparable to those of the functional psy2a promoters. Semi-quantitative PCR analysis of Asupina and Cavendish psy1 and psy2a transcripts showed that psy2a levels were high in green fruit and decreased during ripening, reinforcing the hypothesis that fruit pVA levels were largely dependent on levels of psy2a expression. Additionally, semi-quantitative PCR using intron-spanning primers indicated that high levels of unprocessed psy2a and psy2b mRNA were present in the ripe fruit of Cavendish but not in Asupina. This raised the possibility that differences in intron processing may influence pVA accumulation in Asupina and Cavendish. In this study the role of PSY in banana pVA accumulation was analysed at a number of different levels. Both mRNA accumulation and promoter activity of psy genes studied were very similar between Asupina and Cavendish. However, in several experiments there was evidence of cryptic or alternate splicing that differed in Cavendish compared to Asupina, although these differences were not conclusively linked to the differences in fruit pVA accumulation between Asupina and Cavendish. Therefore, other carotenoid biosynthetic genes or regulatory mechanisms may be involved in determining pVA levels in these cultivars. This study has contributed to an increased understanding of the role of PSY in the production of pVA carotenoids in banana fruit, corroborating the importance of this enzyme in regulating carotenoid production. Ultimately, this work may serve to inform future research into pVA accumulation in important crop varieties such as the EAHB and the discovery of avenues to improve such crops through genetic modification.