This thesis presents the results of an investigation into the structural protein, tubulin, as a potential target for anti-trypanosomatid drug discovery and vaccine development. Recombinant alpha- and beta- tubulin proteins from Trypanosoma brucei rhodesiense were expressed as soluble fusion proteins in an E. coli expression system. The recombinant alpha- and beta- tubulins were used to determine the nature of binding of novel trifluralin analogues EPL-AJ 1003, 1007, 1008, 1016 and 1017. Native tubulin from rats was used to determine the extent of binding to mammalian tubulin. The results of this study clearly demonstrate two important aspects of the binding of trifluralins to tubulin. Firstly, they have specific affinity for trypanosomal tubulin compared with mammalian regardless of the chemical composition of the trifluralin analogue tested. Secondly, they have a demonstrably stronger affinity for alpha-tubulin compared with beta-tubulin. In addition, compounds 1007, 1008, 1016 and 1017 have strong binding affinities for alpha-tubulin, with limited binding affinity for mammalian tubulin, which indicates that these compounds selectively bind to trypanosomal tubulin. The morphology of bloodstream forms of T. b. rhodesiense exposed to trifluralin analogues was studied using electron microscopy and immunofluorescence to determine the ultrastructural changes these compounds induce as a result of binding to tubulin. All compounds tested induced severe irreparable damage in T. b. rhodesiense, including perturbation of subpellicular microtubules, extensive cytoplasmic swellings, axoneme and paraflagellar rod malformation, disconfiguration around the flagellar pocket and membrane disintegration. These results suggest that the mechanism of action of these trifluralin analogues is through the disruption of polymerization of tubulin into microtubules as a result of binding to alpha-tubulin. The potential for recombinant trypanosomal tubulins to be used as vaccine candidates was assessed by monitoring parasitaemia and length of survival of mice immunised with the proteins and challenged with a lethal infection of T. b. rhodesiense. Although all the mice vaccinated with recombinant tubulin developed a patent parasitaemia and did not survive, they were partially protected because their patency period and length of survival were significantly greater than the control groups. Furthermore, plasma collected from mice immunised with recombinant trypanosomal tubulin contained antibodies that recognized tubulin in a soluble extraction from T. b. rhodesiense. The results of this thesis confirm the potential for the structural protein, tubulin, to be used as a target for anti-trypanosomatid drug discovery and vaccine development.

Recent technological advancements are enabling the vision of pervasive or ubiquitous computing to become a reality. Service discovery is vital in such a computing paradigm, where a great number of devices and software components collaborate unobtrusively and provide numerous services. Current service-discovery protocols do not make use of contextual information in discovering services, and as a result, fail to provide the most appropriate and relevant services for users. In addition, current protocols rely on keyword-based search techniques and do not consider the semantic description of services. Thus, they suffer from poor precision and recall. To address the need for a discovery architecture that supports the envisioned scenarios of pervasive computing, we propose a context-aware service-discovery protocol that exploits meaningful contextual information, either static or dynamic, to provide users with the most suitable and relevant services. The architecture relies on a shared, ontology-based, semantic representation of services and context to enhance precision and recall, and to enable knowledge sharing, capability-based search, autonomous reasoning, and semantic matchmaking. Furthermore, the architecture facilitates a dynamic service-selection mechanism to filter and rank matching services, based on their dynamic contextual attributes, which further enhances the discovery process and saves users time and effort. Our empirical results indicate the effectiveness and feasibility of the proposed architecture.

Recent technological advancements are enabling the vision of pervasive or ubiquitous computing to become a reality. Service discovery is vital in such a computing paradigm, where a great number of devices and software components collaborate unobtrusively and provide numerous services. Current service-discovery protocols do not make use of contextual information in discovering services, and as a result, fail to provide the most appropriate and relevant services for users. In addition, current protocols rely on keyword-based search techniques and do not consider the semantic description of services. Thus, they suffer from poor precision and recall. To address the need for a discovery architecture that supports the envisioned scenarios of pervasive computing, we propose a context-aware service-discovery protocol that exploits meaningful contextual information, either static or dynamic, to provide users with the most suitable and relevant services. The architecture relies on a shared, ontology-based, semantic representation of services and context to enhance precision and recall, and to enable knowledge sharing, capability-based search, autonomous reasoning, and semantic matchmaking. Furthermore, the architecture facilitates a dynamic service-selection mechanism to filter and rank matching services, based on their dynamic contextual attributes, which further enhances the discovery process and saves users time and effort. Our empirical results indicate the effectiveness and feasibility of the proposed architecture.

In June, 1959, I entered into a contract with the United States Atomic Energy Commission (Contract No. AT(04-3-315) to direct a programme of human geographical studies in Northwestern Arctic Alaska. These studies were part of the bio-environmental programme for Project Chariot. They were centred on the Eskimo village of Point Hope but included the villages of Noatak and Point Lay. Although the contract terminated on June 1st, 1961 I remained in arctic Alaska for an additiona1 year of research. [...]

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Finding frequent patterns plays a vital role in many analytics tasks such as finding itemsets, associations, correlations, and sequences. In recent decades, spatiotemporal frequent pattern mining has emerged with the main goal focused on developing data-driven analysis frameworks for understanding underlying spatial and temporal characteristics in massive datasets. In this thesis, we will focus on discovering spatiotemporal event sequences from large-scale region trajectory datasetes with event annotations. Spatiotemporal event sequences are the series of event types whose trajectory-based instances follow each other in spatiotemporal context. We introduce new data models for storing and processing evolving region trajectories, provide a novel framework for modeling spatiotemporal follow relationships, and present novel spatiotemporal event sequence mining algorithms.

This thesis describes the development and refinement of a number of techniques for molecular docking and ligand database screening, as well as the application of these techniques to predict the structures of several protein-ligand complexes and to discover novel ligands of an important receptor protein. Global energy optimisation by Monte-Carlo minimisation in internal co-ordinates was used to predict bound conformations of eight protein-ligand complexes. Experimental X-ray crystallography structures became available after the predictions were made. Comparison with the X-ray structures showed that the docking procedure placed 30 to 70% of the ligand molecule correctly within 1.5A from the native structure. The discrimination potential for identification of high-affinity ligands was derived and optimised using a large set of available protein-ligand complex structures. A fast boundary-element solvation electrostatic calculation algorithm was implemented to evaluate the solvation component of the discrimination potential. An accelerated docking procedure utilising pre-calculated grid potentials was developed and tested. For 23 receptors and 63 ligands extracted from X-ray structures, the docking and discrimination protocol was capable of correct identification of the majority of native receptor-ligand couples. 51 complexes with known structures were predicted. 35 predictions were within 3A from the native structure, giving correct overall positioning of the ligand, and 26 were within 2A, reproducing a detailed picture of the receptor-ligand interaction. Docking and ligand discrimination potential evaluation was applied to screen the database of more than 150000 commercially available compounds for binding to the fibroblast growth factor receptor tyrosine kinase, the protein implicated in several pathological cell growth aberrations. As expected, a number of compounds selected by the screening protocol turned out to be known inhibitors of the tyrosine kinases. 49 putative novel ligands identified by the screening protocol were experimentally tested and five compounds have shown inhibition of phosphorylation activity of the kinase. These compounds can be used as leads for further drug development.

AMANDA-II est un télescope à neutrinos composé d'un réseau tri-dimensionnel de senseurs optiques déployé dans la glace du Pôle Sud. Son principe de détection repose sur la mise en évidence de particules secondaires chargées émises lors de l'interaction d'un neutrino de haute énergie (> 100 GeV) avec la matière environnant le détecteur, sur base de la détection de rayonnement Cerenkov. Ce travail est basé sur les données enregistrées par AMANDA-II entre 2000 et 2006, afin de rechercher des sources cosmiques de neutrinos. Le signal recherché est affecté d'un bruit de fond important de muons et de neutrinos issus de l'interaction du rayonnement cosmique primaire dans l'atmosphère. En se limitant à l'observation de l'hémisphère nord, le bruit de fond des muons atmosphériques, absorbés par la Terre, est éliminé. Par contre, les neutrinos atmosphériques forment un bruit de fond irréductible constituant la majorité des 6100 événements sélectionnés pour cette analyse. Il est cependant possible d'identifier une source ponctuelle de neutrinos cosmiques en recherchant un excès local se détachant du bruit de fond isotrope de neutrinos atmosphériques, couplé à une sélection basée sur l'énergie, dont le spectre est différent pour les deux catégories de neutrinos. Une approche statistique originale est développée dans le but d'optimiser le pouvoir de détection de sources ponctuelles, tout en contrôlant le taux de fausses découvertes, donc le niveau de confiance d'une observation. Cette méthode repose uniquement sur la connaissance de l'hypothèse de bruit de fond, sans aucune hypothèse sur le modèle de production de neutrinos par les sources recherchées. De plus, elle intègre naturellement la notion de facteur d'essai rencontrée dans le cadre de test d'hypothèses multiples.La procédure a été appliquée sur l'échantillon final d'évènements récoltés par AMANDA-II. --------- MANDA-II is a neutrino telescope which comprises a three dimensional array of optical sensors deployed in the South Pole glacier. Its principle rests on the detection of the Cherenkov radiation emitted by charged secondary particles produced by the interaction of a high energy neutrino (> 100 GeV) with the matter surrounding the detector. This work is based on data recorded by the AMANDA-II detector between 2000 and 2006 in order to search for cosmic sources of neutrinos. A potential signal must be extracted from the overwhelming background of muons and neutrinos originating from the interaction of primary cosmic rays within the atmosphere. The observation is limited to the northern hemisphere in order to be free of the atmospheric muon background, which is stopped by the Earth. However, atmospheric neutrinos constitute an irreducible background composing the main part of the 6100 events selected for this analysis. It is nevertheless possible to identify a point source of cosmic neutrinos by looking for a local excess breaking away from the isotropic background of atmospheric neutrinos; This search is coupled with a selection based on the energy, whose spectrum is different from that of the atmospheric neutrino background. An original statistical approach has been developed in order to optimize the detection of point sources, whilst controlling the false discovery rate -- hence the confidence level -- of an observation. This method is based solely on the knowledge of the background hypothesis, without any assumption on the production model of neutrinos in sought sources. Moreover, the method naturally accounts for the trial factor inherent in multiple testing.The procedure was applied on the final sample of events collected by AMANDA-II.