Comparing protein structures based on their contact maps is an important problem in structural proteomics. Building a system for reconstructing protein tertiary structures from their contact maps is one of the motivations for devising novel contact map comparison algorithms. Several methods that address the contact map comparison problem have been designed which are briefly discussed in this thesis. However, they suggest scoring schemes that do not satisfy the two characteristics of “metricity” and “universality”. In this research we investigate the applicability of the Universal Similarity Metric (USM) to the contact map comparison problem. The USM is an information theoretical measure which is based on the concept of Kolmogorov complexity. The ultimate goal of this research is to use the USM in case-based reasoning system to predict protein structures from their predicted contact maps. The fact that the contact maps that will be used in such a system are the ones which are predicted from the protein sequences and are not noise-free, implies that we should investigate the noise-sensitivity of the USM. This is the first attempt to study the noise-tolerance of the USM. In this research, as the first implementation of the USM we converted the two-dimensional data structures (contact maps) to one-dimensional data structures (strings). The results of this implementation motivated us to circumvent the dimension reduction in our second attempt to implement the USM. Our suggested method in this thesis has the advantage of obtaining a measure which is noise tolerant. We assess the effectiveness of this noise tolerance by testing different USM implementation schemes against noise-contaminated versions of distinguished data-sets. / Thesis (Master, Computing) -- Queen's University, 2008-09-27 05:53:31.988

A Stroke can affect different parts of the human body depending on the area of brain effected; our research focuses on upper limb motor dysfunction for stroke patients. In current practice, ordinal scale systems are used for conducting physical assessment of upper limb impairment. The reliability of these assessments is questionable, since their coarse ratings cannot reliably distinguish between the different levels of performance. This thesis describes the design, implementation and evaluation of a novel system to facilitate stroke diagnosis which relies on data collected with an innovative KINARM robotic tool. This robotic tool allows for an objective quantification of motor function and performance assessment for stroke patients. The main methodology for the research is Case Based Reasoning (CBR) - an effective paradigm of artificial intelligence that relies on the principle that a new problem is solved by observing similar, previously encountered problems and adapting their known solutions. A CBR system was designed and implemented for a repository of stroke subjects who had an explicit diagnosis and prognosis. For a new stroke patient, whose diagnosis was yet to be confirmed and who had an indefinite prognosis, the CBR model was effectively used to retrieve analogous cases of previous stroke patients. These similar cases provide useful information to the clinicians, facilitating them in reaching a potential solution for stroke diagnosis and also a means to validate other imaging tests and clinical assessments to confirm the diagnosis and prognosis. / Thesis (Master, Computing) -- Queen's University, 2008-09-27 11:14:04.85

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No description available.

The purpose of this thesis is to contribute to the methodology at the intersection of relational and evaluative bibliometrics. Experimental investigations are presented that address the question of how we can most successfully produce estimates of the subject similarity between documents. The results from these investigations are then explored in the context of citation-based research evaluations in an effort to enhance existing citation normalization methods that are used to enable comparisons of subject-disparate documents with respect to their relative impact or perceived utility. This thesis also suggests and explores an approach for revealing the uncertainty and stability (or lack thereof) coupled with different kinds of citation indicators.This suggestion is motivated by the specific nature of the bibliographic data and the data collection process utilized in citation-based evaluation studies. The results of these investigations suggest that similarity-detection methods that take a global view of the problem of identifying similar documents are more successful in solving the problem than conventional methods that are more local in scope. These results are important for all applications that require subject similarity estimates between documents. Here these insights are specifically adopted in an effort to create a novel citation normalization approach that – compared to current best practice – is more in tune with the idea of controlling for subject matter when thematically different documents are assessed with respect to impact or perceived utility. The normalization approach is flexible with respect to the size of the normalization baseline and enables a fuzzy partition of the scientific literature. It is shown that this approach is more successful than currently applied normalization approaches in reducing the variability in the observed citation distribution that stems from the variability in the articles’ addressed subject matter. In addition, the suggested approach can enhance the interpretability of normalized citation counts. Finally, the proposed method for assessing the stability of citation indicators stresses that small alterations that could be artifacts from the data collection and preparation steps can have a significant influence on the picture that is painted by the citationindicator. Therefore, providing stability intervals around derived indicators prevents unfounded conclusions that otherwise could have unwanted policy implications. Together, the new normalization approach and the method for assessing the stability of citation indicators have the potential to enable fairer bibliometric evaluative exercises and more cautious interpretations of citation indicators.

We present a novel approach for deriving analytical solutions to transport equations expressedin similarity variables. We apply a fixed-point iteration procedure to these transformedequations by formally solving for the highest derivative term and then integrating to obtainan expression for the solution in terms of a previous estimate. We are able to analyticallyobtain the Lipschitz condition for this iteration procedure and, from this (via requirements forconvergence given by the contraction mapping principle), deduce a range of values for the outerlimit of the solution domain, for which the fixed-point iteration is guaranteed to converge.

Simultaneous measurement of the expression levels of thousands to ten thousand genes in multiple tissue types is a result of advancement in microarray technology. These expression levels provide clues about the gene functions and that have enabled better diagnosis and treatment of serious disease like cancer. To solve the mystery of unknown gene functions, biological to statistical mapping is needed in terms of classifying the genes. Here we introduce a novel approach of combining both statistical consistency and biological relevance of the clusters produced by a clustering method. Here we employ two performance measures in combination for measuring statistical stability and functional similarity of the cluster members using a set of gene expressions with known biological functions. Through this analysis we construct a platform to predict about unknown gene functions using the outperforming clustering algorithm.

Genitourinary cancer refers to the presence of tumours in the genital or urinary organs such as bladder, kidney and prostate. In 2008 the worldwide incidence of bladder cancer was 382,600 with a mortality of 150,282. Radiotherapy is one of the main treatment choices for genitourinary cancer where accurate delineation of the gross tumour volume (GTV) on computed tomography (CT) images is crucial for the success of this treatment. Limited CT resolution and contrast in soft tissue organs make this difficult and has led to significant inter- and intra- clinical variability in defining the extent of the GTV, especially at the junctions of different organs. In addition the introduction of new imaging techniques and modalities has significantly increased the number of the medical images that require contouring. More advanced image processing is required to help reduce contouring variability and assist in handling the increased volume of data. In this thesis image analysis methodologies were used to extract low-level features such as entropy, moment and correlation from radiotherapy planning CT images. These distinctive features were identified and used for defining the GTV and to implement a fully-automatic contouring system. The first key contribution is to demonstrate that second-order statistics from co-occurrence matrices (GTSDM) give higher accuracy in classifying soft tissue regions of interest (ROIs) into GTV and non-GTV. Loadings of the principal components (PCs) of the GTSDM features were found to be consistent over different patients. Exhaustive feature selection suggested that entropies and correlations produced consistently larger areas under receiver operating characteristic (AUROC) curves than first-order features. The second significant contribution is to demonstrate that in the bladder-prostate junction, where the largest inter-clinical variability is observed, the second-order principal entropy from stationery wavelet denoised CT images (DPE) increased the saliency of the bladder prostate junction. As a result thresholding of the DPE produced good agreement between gold standard clinical contours and those produced by this approach with Dice coefficients. The third contribution is to implement a fully automatic and reproducible system for bladder cancer GTV auto-contouring based on classifying second-order statistics. The Dice similarity coefficients (DSCs) were employed to evaluate the automatic contours. It was found that in the mid-range of the bladder the automatic contours are accurate, but in the inferior and superior ends of bladder automatic contours were more likely to have small DSCs with clinical contours, which reconcile with the fact of clinical variability in defining GTVs. A novel male bladder probability atlas was constructed based on the clinical contours and volume estimation from the classification results. Registration of the classification results with this probabilistic atlas consistently increases the DSCs of the inferior slices.

Fungi and Oomycetes represent the two most important groups of eukaryotic plant pathogens. Besides chemical and physical control of these pathogens, biological control is an approach enjoying increasingly more focus. One of the biological agents increasingly employed in biological control of plant pathogenic fungi is ironically the fungus Trichoderma, more specifically Trichoderma harzianum. Besides control of the fungal plant pathogens, another interesting aspect observed when plants are treated with Trichoderma harzianum are effects such as complete and even stand of plants, faster seed germination, increases in plant height and overall enhanced plant growth. Though there have been various studies on this effect, almost no research has yet been conducted to elucidate the mechanism by which these effects occur. In particular, effects such as faster seed germination suggest that Trichoderma harzianum produces a metabolite that may mimic the plant growth hormone gibberellic acid. Through an evaluation of the various metabolites produced by Trichoderma harzianum; gliotoxin seemed structurally most similar to gibberellic acid. To verify that gliotoxin can indeed serve as an analogue for gibberellic acid and elicit similar physiological responses in plants, a two–pronged approach was followed. Firstly, molecular similarity evaluation through common pharmacophore evaluation was conducted, followed by docking simulations into the recently discovered receptor for gibberellic acid. Common pharmacophore evaluation between gibberellic acid and gliotoxin showed successful alignment of gliotoxin into the gibberellic acid based pharmacophore space. Furthermore, docking simulations further strengthened this by the similarity in docking scores calculated and the similar poses of the ligands (gliotoxin and gibberellic acid) in the receptor space. However, similarity in pharmacophore alignment and docking simulation results only suggest that gliotoxin should be able to occupy the receptor space, but it is not a guarantee that similar physiological responses will be elicited. In the second part of the project, the ability of gliotoxin to elicit similar physiological responses in plants to gibberellic acid was investigated. For this, a–amylase induction; plant emergence and height; and chlorophyll fluorescence were compared for both gliotoxin and gibberellic acid treatments. In terms of a–amylase induction, gliotoxin was able to induce production of the enzyme as visualised by starch–containing native gel electrophoresis (zymograms). Gliotoxin induced the strongest response at a 10–6 M dilution which is typically the range expected for hormones in biological systems in de–embryonated seeds of Phaseolus vulgaris. Gibberellic acid was able to induce the strongest response at a 10–7 M dilution. In essence, similar physiological responses were observed. In terms of plant emergence and plant height, treatment with gliotoxin or gibberellic acid resulted in plant emergence a day earlier than the untreated control. However, even though there were slight differences in plant height favouring the gliotoxin or gibberellic acid treated plants, the differences were not statistically significant. Thus, in this regard similar responses were again observed for both gliotoxin and gibberellic acid treatments. In the final evaluation the effect of gliotoxin and gibberellic acid treatments on the chlorophyll fluorescence of mature plants was investigated. Overall, both gliotoxin and gibberellic acid elicited beneficial effects on plant vitality, expressed through PI(Abs) with the gliotoxin treatment performing better than the equivalent gibberellic acid treatment. Overall, the physiological tests demonstrated that gliotoxin can indeed elicit similar positive physiological responses to gibberellic acid in Phaseolus vulgaris. Furthermore the test used in this project can serve as a standard evaluation bench for screening for gibberellic acid analogues on a laboratory scale before larger scale field trials are considered. / Thesis (Ph.D. (Microbiology))--North-West University, Potchefstroom Campus, 2012.

Humans are experts at understanding what they see. Similarity and analogy play a significant role in making sense of the visual world by forming analogies to similar images encountered previously. Yet, while these acts of visual reasoning may be commonplace, the processes of visual analogy are not yet well understood. In this dissertation, I investigate the utility of representing visual information in a fractal manner for computing visual similarity and analogy. In particular, I develop a computational technique of fractal reasoning for addressing problems of visual similarity and novelty. I illustrate the effectiveness of fractal reasoning on problems of visual similarity and analogy on the Raven’s Progressive Matrices and Miller’s Analogies tests of intelligence, problems of visual novelty and oddity on the Odd One Out test of intelligence, and problems of visual similarity and oddity on the Dehaene test of core geometric reasoning. I show that the performance of my computational model on these various tests is comparable to human performance. Fractal reasoning provides a new method for computing answers to such problems. Specifically, I show that the choice of the level of abstraction of problem representation determines the degree to which an answer may be regarded as confident, and that that choice of abstraction may be controlled automatically by the algorithm as a means of seeking that confident answer. This emergence of ambiguity and its remedy via problem re-representation is afforded by the fractal representation. I also show how reasoning over sparse data (at coarse levels of abstraction) or homogeneous data (at finest levels of abstraction) could both drive the automatic exclusion of certain levels of abstraction, as well as provide a signal to shift the analogical reasoning from consideration of simple analogies (such as analogies between pairs of objects) to more complex analogies (such as analogies among triplets, or larger groups of objects). My dissertation also explores fractal reasoning in perception, including both biologically-inspired imprinting and bistable perception. In particular, it provides a computational explanation of bistable perception in the famous Necker cube problem that is directly tied to the process of determining a confident interpretation via re-representation. Thus, my research makes two primary contributions to AI theories of visual similarity and analogy. The first contribution is the Extended Analogy By Recall (ABR*) algorithm, the computational technique for visual reasoning that automatically adjusts fractal representations to an appropriate level of abstraction. The second contribution is the fractal representation itself, a knowledge representation that add the notion of self-similarity and re-representation to analogy making.