34 research outputs found

    An Approach to Overloading With Polymorphism

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    One of the principal characterising features of a programming language is its type system. Many recent functional programming languages adopt a Hindley-Milner style type system facilitating parametric polymorphism. One of the forms of polymorphism found most commonly in programming languages is overloading. Whereas one may consider the Hindley-Milner system an off-the-shelf package for parametric polymorphism, there is no similar uniformity in the approaches taken to overloading. This thesis extends the standard Hindley-Milner system. A type system incorporating parametric polymorphism and overloading is presented both formally and informally, and it is shown to satisfy a principal type theorem. The Hindley-Milner type inference algorithm is extended for the new system. This algorithm is shown to be sound and complete. The characteristic feature of parametric polymorphism is that the same code can be used at many different types. The corresponding characterisation rule for overloading is that different code is used at different types. As such, meaning is assigned to terms on the basis of their typing. The semantics of the form of overloading described herein is assigned by means of a derivation to derivation translation scheme. This scheme is shown to be sound and, under certain well-defined conditions, coherent. This approach to overloading is closely related to the lazy functional programming language Haskell's type class mechanism. Some discussion of matters related to the current system, and arising through that project, is given

    On the use of clustering and the MeSH controlled vocabulary to improve MEDLINE abstract search

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    Databases of genomic documents contain substantial amounts of structured information in addition to the texts of titles and abstracts. Unstructured information retrieval techniques fail to take advantage of the structured information available. This paper describes a technique to improve upon traditional retrieval methods by clustering the retrieval result set into two distinct clusters using additional structural information. Our hypothesis is that the relevant documents are to be found in the tightest cluster of the two, as suggested by van Rijsbergen's cluster hypothesis. We present an experimental evaluation of these ideas based on the relevance judgments of the 2004 TREC workshop Genomics track, and the CLUTO software clustering package

    Structural term extraction for expansion of template-based genomic queries

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    This paper describes our experiments run to address the ad hoc task of the TREC 2005 Genomics track. The task topics were expressed with 5 different structures called Generic Topic Templates (GTTs). We hypothesized the presence of GTT-specific structural terms in the free-text fields of documents relevant to a topic instantiated from that same GTT. Our experiments aimed at extracting and selecting candidate structural terms for each GTT. Selected terms were used to expand initial queries and the quality of the term selection was measured by the impact of the expansion on initial search results. The evaluation used the task training topics and the associated relevance information. This paper describes the two term extraction methods used in the experiments and the resulting two runs sent to NIST for evaluation

    Experiments in terabyte searching, genomic retrieval and novelty detection for TREC 2004

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    In TREC2004, Dublin City University took part in three tracks, Terabyte (in collaboration with University College Dublin), Genomic and Novelty. In this paper we will discuss each track separately and present separate conclusions from this work. In addition, we present a general description of a text retrieval engine that we have developed in the last year to support our experiments into large scale, distributed information retrieval, which underlies all of the track experiments described in this document

    Behavioural Differences in Dogs with Atopic Dermatitis Suggest Stress Could Be a Significant Problem Associated with Chronic Pruritus

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    Canine atopic dermatitis (cAD) is a common allergic skin condition in dogs that causes chronic pruritus. The overall quality of life in dogs with cAD is known to be reduced, and human patients with pruritic conditions report significant psychological burdens from pruritus-induced stress, and atopic dermatitis is associated with significant psychopathological morbidities. We tested the hypothesis that dogs with cAD would display more problem behaviours that could be indicative of stress than would healthy controls. Behavioural data were gathered directly from owners using a validated dog behaviour questionnaire for 343 dogs with a diagnosis of cAD and 552 healthy controls, and scores were also provided for their dog’s pruritus severity. Regression modelling, controlling for potential confounding variables (age, sex, breed, neuter status or other health problem(s)) showed for the first time that pruritus severity in dogs with cAD was associated with increased frequency of behaviours often considered problematic, such as mounting, chewing, hyperactivity, coprophagia, begging for and stealing food, attention-seeking, excitability, excessive grooming, and reduced trainability. Whilst causality cannot be ascertained from this study, the behaviours that were associated with pruritus severity are redirected, self/environment-directed displacement behaviours, which are often considered indicative of stress. Further investigation is warranted, and stress reduction could be helpful when treating dogs with cAD

    The utility of low-density genotyping for imputation in the Thoroughbred horse

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    BACKGROUND: Despite the dramatic reduction in the cost of high-density genotyping that has occurred over the last decade, it remains one of the limiting factors for obtaining the large datasets required for genomic studies of disease in the horse. In this study, we investigated the potential for low-density genotyping and subsequent imputation to address this problem. RESULTS: Using the haplotype phasing and imputation program, BEAGLE, it is possible to impute genotypes from low- to high-density (50K) in the Thoroughbred horse with reasonable to high accuracy. Analysis of the sources of variation in imputation accuracy revealed dependence both on the minor allele frequency of the single nucleotide polymorphisms (SNPs) being imputed and on the underlying linkage disequilibrium structure. Whereas equidistant spacing of the SNPs on the low-density panel worked well, optimising SNP selection to increase their minor allele frequency was advantageous, even when the panel was subsequently used in a population of different geographical origin. Replacing base pair position with linkage disequilibrium map distance reduced the variation in imputation accuracy across SNPs. Whereas a 1K SNP panel was generally sufficient to ensure that more than 80% of genotypes were correctly imputed, other studies suggest that a 2K to 3K panel is more efficient to minimize the subsequent loss of accuracy in genomic prediction analyses. The relationship between accuracy and genotyping costs for the different low-density panels, suggests that a 2K SNP panel would represent good value for money. CONCLUSIONS: Low-density genotyping with a 2K SNP panel followed by imputation provides a compromise between cost and accuracy that could promote more widespread genotyping, and hence the use of genomic information in horses. In addition to offering a low cost alternative to high-density genotyping, imputation provides a means to combine datasets from different genotyping platforms, which is becoming necessary since researchers are starting to use the recently developed equine 70K SNP chip. However, more work is needed to evaluate the impact of between-breed differences on imputation accuracy
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