948 resultados para local sequence alignment problem
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When a flash is presented aligned with a moving stimulus, the former is perceived to lag behind the latter (the flash-lag effect). We study whether this mislocalization occurs when a positional judgment is not required, but a veridical spatial relationship between moving and flashed stimuli is needed to perceive a global shape. To do this, we used Glass patterns that are formed by pairs of correlated dots. One dot of each pair was presented moving and, at a given moment, the other dot of each pair was flashed in order to build the Glass pattern. If a flash-lag effect occurs between each pair of dots, we expect the best perception of the global shape to occur when the flashed dots are presented before the moving dots arrive at the position that physically builds the Glass pattern. Contrary to this, we found that the best detection of Glass patterns occurred for the situation of physical alignment. This result is not consistent with a low-level contribution to the flash-lag effect.
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A visual SLAM system has been implemented and optimised for real-time deployment on an AUV equipped with calibrated stereo cameras. The system incorporates a novel approach to landmark description in which landmarks are local sub maps that consist of a cloud of 3D points and their associated SIFT/SURF descriptors. Landmarks are also sparsely distributed which simplifies and accelerates data association and map updates. In addition to landmark-based localisation the system utilises visual odometry to estimate the pose of the vehicle in 6 degrees of freedom by identifying temporal matches between consecutive local sub maps and computing the motion. Both the extended Kalman filter and unscented Kalman filter have been considered for filtering the observations. The output of the filter is also smoothed using the Rauch-Tung-Striebel (RTS) method to obtain a better alignment of the sequence of local sub maps and to deliver a large-scale 3D acquisition of the surveyed area. Synthetic experiments have been performed using a simulation environment in which ray tracing is used to generate synthetic images for the stereo system
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Top predator loss is a major global problem, with a current trend in biodiversity loss towards high trophic levels that modifies most ecosystems worldwide. Most research in this area is focused on large-bodied predators, despite the high extinction risk of small-bodied freshwater fish that often act as apex consumers. Consequently, it remains unknown if intermittent streams are affected by the consequences of top-predators' extirpations. The aim of our research was to determine how this global problem affects intermittent streams and, in particular, if the loss of a small-bodied top predator (1) leads to a 'mesopredator release', affects primary consumers and changes whole community structures, and (2) triggers a cascade effect modifying the ecosystem function. To address these questions, we studied the topdown effects of a small endangered fish species, Barbus meridionalis (the Mediterranean barbel), conducting an enclosure/exclosure mesocosm experiment in an intermittent stream where B. meridionalis became locally extinct following a wildfire.We found that top predator absence led to 'mesopredator release', and also to 'prey release' despite intraguild predation, which contrasts with traditional food web theory. In addition, B. meridionalis extirpation changed whole macroinvertebrate community composition and increased total macroinvertebrate density. Regarding ecosystem function, periphyton primary production decreased in apex consumer absence. In this study, the apex consumer was functionally irreplaceable; its local extinction led to the loss of an important functional role that resulted in major changes to the ecosystem's structure and function. This study evidences that intermittent streams can be affected by the consequences of apex consumers' extinctions, and that the loss of small-bodied top predators can lead to large ecosystem changes. We recommend the reintroduction of small-bodied apex consumers to systems where they have been extirpated, to restore ecosystem structure and function.
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The usage of digital content, such as video clips and images, has increased dramatically during the last decade. Local image features have been applied increasingly in various image and video retrieval applications. This thesis evaluates local features and applies them to image and video processing tasks. The results of the study show that 1) the performance of different local feature detector and descriptor methods vary significantly in object class matching, 2) local features can be applied in image alignment with superior results against the state-of-the-art, 3) the local feature based shot boundary detection method produces promising results, and 4) the local feature based hierarchical video summarization method shows promising new new research direction. In conclusion, this thesis presents the local features as a powerful tool in many applications and the imminent future work should concentrate on improving the quality of the local features.
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Measles virus is a highly contagious agent which causes a major health problem in developing countries. The viral genomic RNA is single-stranded, nonsegmented and of negative polarity. Many live attenuated vaccines for measles virus have been developed using either the prototype Edmonston strain or other locally isolated measles strains. Despite the diverse geographic origins of the vaccine viruses and the different attenuation methods used, there was remarkable sequence similarity of H, F and N genes among all vaccine strains. CAM-70 is a Japanese measles attenuated vaccine strain widely used in Brazilian children and produced by Bio-Manguinhos since 1982. Previous studies have characterized this vaccine biologically and genomically. Nevertheless, only the F, H and N genes have been sequenced. In the present study we have sequenced the remaining P, M and L genes (approximately 1.6, 1.4 and 6.5 kb, respectively) to complete the genomic characterization of CAM-70 and to assess the extent of genetic relationship between CAM-70 and other current vaccines. These genes were amplified using long-range or standard RT-PCR techniques, and the cDNA was cloned and automatically sequenced using the dideoxy chain-termination method. The sequence analysis comparing previously sequenced genotype A strains with the CAM-70 Bio-Manguinhos strain showed a low divergence among them. However, the CAM-70 strains (CAM-70 Bio-Manguinhos and a recently sequenced CAM-70 submaster seed strain) were assigned to a specific group by phylogenetic analysis using the neighbor-joining method. Information about our product at the genomic level is important for monitoring vaccination campaigns and for future studies of measles virus attenuation.
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Our objective was to clone, express and characterize adult Dermatophagoides farinae group 1 (Der f 1) allergens to further produce recombinant allergens for future clinical applications in order to eliminate side reactions from crude extracts of mites. Based on GenBank data, we designed primers and amplified the cDNA fragment coding for Der f 1 by nested-PCR. After purification and recovery, the cDNA fragment was cloned into the pMD19-T vector. The fragment was then sequenced, subcloned into the plasmid pET28a(+), expressed in Escherichia coli BL21 and identified by Western blotting. The cDNA coding for Der f 1 was cloned, sequenced and expressed successfully. Sequence analysis showed the presence of an open reading frame containing 966 bp that encodes a protein of 321 amino acids. Interestingly, homology analysis showed that the Der p 1 shared more than 87% identity in amino acid sequence with Eur m 1 but only 80% with Der f 1. Furthermore, phylogenetic analyses suggested that D. pteronyssinus was evolutionarily closer to Euroglyphus maynei than to D. farinae, even though D. pteronyssinus and D. farinae belong to the same Dermatophagoides genus. A total of three cysteine peptidase active sites were found in the predicted amino acid sequence, including 127-138 (QGGCGSCWAFSG), 267-277 (NYHAVNIVGYG) and 284-303 (YWIVRNSWDTTWGDSGYGYF). Moreover, secondary structure analysis revealed that Der f 1 contained an a helix (33.96%), an extended strand (17.13%), a ß turn (5.61%), and a random coil (43.30%). A simple three-dimensional model of this protein was constructed using a Swiss-model server. The cDNA coding for Der f 1 was cloned, sequenced and expressed successfully. Alignment and phylogenetic analysis suggests that D. pteronyssinus is evolutionarily more similar to E. maynei than to D. farinae.
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Apoptotic beta cell death is an underlying cause majorly for type I and to a lesser extent for type II diabetes. Recently, MST1 kinase was identified as a key apoptotic agent in diabetic condition. In this study, I have examined MST1 and closely related kinases namely, MST2, MST3 and MST4, aiming to tackle diabetes by exploring ways to selectively block MST1 kinase activity. The first investigation was directed towards evaluating possibilities of selectively blocking the ATP binding site of MST1 kinase that is essential for the activity of the enzymes. Structure and sequence analyses of this site however revealed a near absolute conservation between the MSTs and very few changes with other kinases. The observed residue variations also displayed similar physicochemical properties making it hard for selective inhibition of the enzyme. Second, possibilities for allosteric inhibition of the enzyme were evaluated. Analysis of the recognized allosteric site also posed the same problem as the MSTs shared almost all of the same residues. The third analysis was made on the SARAH domain, which is required for the dimerization and activation of MST1 and MST2 kinases. MST3 and MST4 lack this domain, hence selectivity against these two kinases can be achieved. Other proteins with SARAH domains such as the RASSF proteins were also examined. Their interaction with the MST1 SARAH domain were evaluated to mimic their binding pattern and design a peptide inhibitor that interferes with MST1 SARAH dimerization. In molecular simulations the RASSF5 SARAH domain was shown to strongly interact with the MST1 SARAH domain and possibly preventing MST1 SARAH dimerization. Based on this, the peptidic inhibitor was suggested to be based on the sequence of RASSF5 SARAH domain. Since the MST2 kinase also interacts with RASSF5 SARAH domain, absolute selectivity might not be achieved.
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The quality of the mother-child relationship was examined in relation to joint planning, maternal teaching strategies, maternal emotional support, mutual positive affect and attachment security. Fifty-five grade five children and their mothers participated in a laboratory session comprised of various activities and completed questionnaires to evaluate attachment security. Joint planning and social problem solving were assessed observationally during an origami task. Problem solving effectiveness was unrelated to maternal teaching strategies, maternal encouragement and mutual positive affect. A marginally significant relationship was found between maternal encouragement and active child participation. Attachment security was found to be significantly related to sharing of responsibility during local planning, but only for child autonomous performance. An examination of conditional probabilities revealed that mutual positive affect did not increase the likelihood of subsequent mother-child dyadic regulation. However, mutual positive affect was found to be significantly related to both active child participation and dyadic regulation. The hypothesis predicting a mediational model was not supported. The implications of these findings in the theoretical and empirical literature were considered and suggestions for future research were made.
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Complex networks have recently attracted a significant amount of research attention due to their ability to model real world phenomena. One important problem often encountered is to limit diffusive processes spread over the network, for example mitigating pandemic disease or computer virus spread. A number of problem formulations have been proposed that aim to solve such problems based on desired network characteristics, such as maintaining the largest network component after node removal. The recently formulated critical node detection problem aims to remove a small subset of vertices from the network such that the residual network has minimum pairwise connectivity. Unfortunately, the problem is NP-hard and also the number of constraints is cubic in number of vertices, making very large scale problems impossible to solve with traditional mathematical programming techniques. Even many approximation algorithm strategies such as dynamic programming, evolutionary algorithms, etc. all are unusable for networks that contain thousands to millions of vertices. A computationally efficient and simple approach is required in such circumstances, but none currently exist. In this thesis, such an algorithm is proposed. The methodology is based on a depth-first search traversal of the network, and a specially designed ranking function that considers information local to each vertex. Due to the variety of network structures, a number of characteristics must be taken into consideration and combined into a single rank that measures the utility of removing each vertex. Since removing a vertex in sequential fashion impacts the network structure, an efficient post-processing algorithm is also proposed to quickly re-rank vertices. Experiments on a range of common complex network models with varying number of vertices are considered, in addition to real world networks. The proposed algorithm, DFSH, is shown to be highly competitive and often outperforms existing strategies such as Google PageRank for minimizing pairwise connectivity.
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Affiliation: Département de biochimie, Faculté de médecine, Université de Montréal
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Cet article discute des problèmes de gouvernance et de corruption en Afrique dans le cadre d’un débat politique et philosophique large entre universalisme et relativisme, idéalisme et réalisme, ainsi que entre individualisme et communautarisme. Premièrement, je défends que l’approche réaliste de l’éthique politique et du leadership ne permet pas de différencier entre les éléments descriptifs et prescriptifs de la gouvernance et peut aisément être utilisée pour justifier « les Mains Sales » des dirigeants au nom de l’intérêt supérieur de la nation, même dans les cas où l’intérêt personnel est la seule force motivationnelle pour les actions qui sapent les codes sociaux et éthiques ordinaires. Deuxièmement, l’article montre la faillite de la confiance publique dans le gouvernement et la faiblesse de l’Etat renforce les politiques communautariennes sub-nationales qui tendent à être fondées sur l’ethnie et exclusive, et par conséquent, qui viole le cœur de l’éthique publique, c’est-à-dire l’impartialité. Finalement, l’article suggère que les principes d’éthique universels pour les services publiques soient introduits en complément plutôt qu’en concurrence avec les éthiques locales, socialement et culturellement limitée au privé. Cela requière, d’une part, que nous comprenions mieux la complexité historique, les circonstances économiques et sociales et les arrangements politiques transitionnels dans les pays africains. D’autre part, un nous devons investir dans une éducation éthique civique et professionnel réflexive qui adopte un point de vue nuancé entre le réalisme politique et l’idéalisme comme point de départ des réformes institutionnelles, aussi bien que modalité de changement des comportements à long terme.
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Lors d'une intervention conversationnelle, le langage est supporté par une communication non-verbale qui joue un rôle central dans le comportement social humain en permettant de la rétroaction et en gérant la synchronisation, appuyant ainsi le contenu et la signification du discours. En effet, 55% du message est véhiculé par les expressions faciales, alors que seulement 7% est dû au message linguistique et 38% au paralangage. L'information concernant l'état émotionnel d'une personne est généralement inférée par les attributs faciaux. Cependant, on ne dispose pas vraiment d'instruments de mesure spécifiquement dédiés à ce type de comportements. En vision par ordinateur, on s'intéresse davantage au développement de systèmes d'analyse automatique des expressions faciales prototypiques pour les applications d'interaction homme-machine, d'analyse de vidéos de réunions, de sécurité, et même pour des applications cliniques. Dans la présente recherche, pour appréhender de tels indicateurs observables, nous essayons d'implanter un système capable de construire une source consistante et relativement exhaustive d'informations visuelles, lequel sera capable de distinguer sur un visage les traits et leurs déformations, permettant ainsi de reconnaître la présence ou absence d'une action faciale particulière. Une réflexion sur les techniques recensées nous a amené à explorer deux différentes approches. La première concerne l'aspect apparence dans lequel on se sert de l'orientation des gradients pour dégager une représentation dense des attributs faciaux. Hormis la représentation faciale, la principale difficulté d'un système, qui se veut être général, est la mise en œuvre d'un modèle générique indépendamment de l'identité de la personne, de la géométrie et de la taille des visages. La démarche qu'on propose repose sur l'élaboration d'un référentiel prototypique à partir d'un recalage par SIFT-flow dont on démontre, dans cette thèse, la supériorité par rapport à un alignement conventionnel utilisant la position des yeux. Dans une deuxième approche, on fait appel à un modèle géométrique à travers lequel les primitives faciales sont représentées par un filtrage de Gabor. Motivé par le fait que les expressions faciales sont non seulement ambigües et incohérentes d'une personne à une autre mais aussi dépendantes du contexte lui-même, à travers cette approche, on présente un système personnalisé de reconnaissance d'expressions faciales, dont la performance globale dépend directement de la performance du suivi d'un ensemble de points caractéristiques du visage. Ce suivi est effectué par une forme modifiée d'une technique d'estimation de disparité faisant intervenir la phase de Gabor. Dans cette thèse, on propose une redéfinition de la mesure de confiance et introduisons une procédure itérative et conditionnelle d'estimation du déplacement qui offrent un suivi plus robuste que les méthodes originales.
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Thèse réalisée en cotutelle entre l'Université de Montréal et l'Université de Technologie de Troyes
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L’importance que revêt la localisation des entreprises dans le fonctionnement et la compétitivité de celles-ci amène à porter l’attention sur la problématique des clusters et l’influence qu’ils peuvent avoir sur la production de connaissances. À travers une perspective théorique qui repose sur la prise en compte des travaux portant sur les districts industriels et ceux plus récents, sur les clusters, nous mettons en évidence une évolution conceptuelle du phénomène de la localisation des entreprises. La place qu’occupe la production de connaissances constitue désormais un élément central des travaux récents qui portent sur les districts et les clusters industriels. Notre examen des dynamiques de fonctionnement de ces systèmes permet d’affirmer que la production de connaissances est une caractéristique centrale des clusters ainsi que leur principal avantage compétitif. Étroitement liée aux réseaux inter-organisationnels, la production de connaissances n’est pas un phénomène naturel, elle découle des mécanismes intrinsèques aux clusters, qu’on cherche à mettre en évidence. Pour ce faire, notre méthodologie qui emprunte les principaux repères de l’analyse stratégique des organisations conduit à l’étude du fonctionnement concret d’un réseau local d’innovation, constitué d’entreprises et d’institutions locales présentes dans le cluster montréalais de l’aérospatiale. Un réseau constitué par l’intermédiaire du Consortium de Recherche et d’Innovation en Aérospatiale du Québec, une institution centrale dans le fonctionnement de ce cluster.
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Computational Biology is the research are that contributes to the analysis of biological data through the development of algorithms which will address significant research problems.The data from molecular biology includes DNA,RNA ,Protein and Gene expression data.Gene Expression Data provides the expression level of genes under different conditions.Gene expression is the process of transcribing the DNA sequence of a gene into mRNA sequences which in turn are later translated into proteins.The number of copies of mRNA produced is called the expression level of a gene.Gene expression data is organized in the form of a matrix. Rows in the matrix represent genes and columns in the matrix represent experimental conditions.Experimental conditions can be different tissue types or time points.Entries in the gene expression matrix are real values.Through the analysis of gene expression data it is possible to determine the behavioral patterns of genes such as similarity of their behavior,nature of their interaction,their respective contribution to the same pathways and so on. Similar expression patterns are exhibited by the genes participating in the same biological process.These patterns have immense relevance and application in bioinformatics and clinical research.Theses patterns are used in the medical domain for aid in more accurate diagnosis,prognosis,treatment planning.drug discovery and protein network analysis.To identify various patterns from gene expression data,data mining techniques are essential.Clustering is an important data mining technique for the analysis of gene expression data.To overcome the problems associated with clustering,biclustering is introduced.Biclustering refers to simultaneous clustering of both rows and columns of a data matrix. Clustering is a global whereas biclustering is a local model.Discovering local expression patterns is essential for identfying many genetic pathways that are not apparent otherwise.It is therefore necessary to move beyond the clustering paradigm towards developing approaches which are capable of discovering local patterns in gene expression data.A biclusters is a submatrix of the gene expression data matrix.The rows and columns in the submatrix need not be contiguous as in the gene expression data matrix.Biclusters are not disjoint.Computation of biclusters is costly because one will have to consider all the combinations of columans and rows in order to find out all the biclusters.The search space for the biclustering problem is 2 m+n where m and n are the number of genes and conditions respectively.Usually m+n is more than 3000.The biclustering problem is NP-hard.Biclustering is a powerful analytical tool for the biologist.The research reported in this thesis addresses the problem of biclustering.Ten algorithms are developed for the identification of coherent biclusters from gene expression data.All these algorithms are making use of a measure called mean squared residue to search for biclusters.The objective here is to identify the biclusters of maximum size with the mean squared residue lower than a given threshold. All these algorithms begin the search from tightly coregulated submatrices called the seeds.These seeds are generated by K-Means clustering algorithm.The algorithms developed can be classified as constraint based,greedy and metaheuristic.Constarint based algorithms uses one or more of the various constaints namely the MSR threshold and the MSR difference threshold.The greedy approach makes a locally optimal choice at each stage with the objective of finding the global optimum.In metaheuristic approaches particle Swarm Optimization(PSO) and variants of Greedy Randomized Adaptive Search Procedure(GRASP) are used for the identification of biclusters.These algorithms are implemented on the Yeast and Lymphoma datasets.Biologically relevant and statistically significant biclusters are identified by all these algorithms which are validated by Gene Ontology database.All these algorithms are compared with some other biclustering algorithms.Algorithms developed in this work overcome some of the problems associated with the already existing algorithms.With the help of some of the algorithms which are developed in this work biclusters with very high row variance,which is higher than the row variance of any other algorithm using mean squared residue, are identified from both Yeast and Lymphoma data sets.Such biclusters which make significant change in the expression level are highly relevant biologically.