931 resultados para Bioinformatics


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MOTIVATION: The anatomy of model species is described in ontologies, which are used to standardize the annotations of experimental data, such as gene expression patterns. To compare such data between species, we need to establish relations between ontologies describing different species. RESULTS: We present a new algorithm, and its implementation in the software Homolonto, to create new relationships between anatomical ontologies, based on the homology concept. Homolonto uses a supervised ontology alignment approach. Several alignments can be merged, forming homology groups. We also present an algorithm to generate relationships between these homology groups. This has been used to build a multi-species ontology, for the database of gene expression evolution Bgee. AVAILABILITY: download section of the Bgee website http://bgee.unil.ch/

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Neurocritical care depends, in part, on careful patient monitoring but as yet there are little data on what processes are the most important to monitor, how these should be monitored, and whether monitoring these processes is cost-effective and impacts outcome. At the same time, bioinformatics is a rapidly emerging field in critical care but as yet there is little agreement or standardization on what information is important and how it should be displayed and analyzed. The Neurocritical Care Society in collaboration with the European Society of Intensive Care Medicine, the Society for Critical Care Medicine, and the Latin America Brain Injury Consortium organized an international, multidisciplinary consensus conference to begin to address these needs. International experts from neurosurgery, neurocritical care, neurology, critical care, neuroanesthesiology, nursing, pharmacy, and informatics were recruited on the basis of their research, publication record, and expertise. They undertook a systematic literature review to develop recommendations about specific topics on physiologic processes important to the care of patients with disorders that require neurocritical care. This review does not make recommendations about treatment, imaging, and intraoperative monitoring. A multidisciplinary jury, selected for their expertise in clinical investigation and development of practice guidelines, guided this process. The GRADE system was used to develop recommendations based on literature review, discussion, integrating the literature with the participants' collective experience, and critical review by an impartial jury. Emphasis was placed on the principle that recommendations should be based on both data quality and on trade-offs and translation into clinical practice. Strong consideration was given to providing pragmatic guidance and recommendations for bedside neuromonitoring, even in the absence of high quality data.

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Cloud computing has recently become very popular, and several bioinformatics applications exist already in that domain. The aim of this article is to analyse a current cloud system with respect to usability, benchmark its performance and compare its user friendliness with a conventional cluster job submission system. Given the current hype on the theme, user expectations are rather high, but current results show that neither the price/performance ratio nor the usage model is very satisfactory for large-scale embarrassingly parallel applications. However, for small to medium scale applications that require CPU time at certain peak times the cloud is a suitable alternative.

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Recently, the introduction of second generation sequencing and further advance-ments in confocal microscopy have enabled system-level studies for the functional characterization of genes. The degree of complexity intrinsic to these approaches needs the development of bioinformatics methodologies and computational models for extracting meaningful biological knowledge from the enormous amount of experi¬mental data which is continuously generated. This PhD thesis presents several novel bioinformatics methods and computational models to address specific biological questions in Plant Biology by using the plant Arabidopsis thaliana as a model system. First, a spatio-temporal qualitative analysis of quantitative transcript and protein profiles is applied to show the role of the BREVIS RADIX (BRX) protein in the auxin- cytokinin crosstalk for root meristem growth. Core of this PhD work is the functional characterization of the interplay between the BRX protein and the plant hormone auxin in the root meristem by using a computational model based on experimental evidence. Hyphotesis generated by the modelled to the discovery of a differential endocytosis pattern in the root meristem that splits the auxin transcriptional response via the plasma membrane to nucleus partitioning of BRX. This positional information system creates an auxin transcriptional pattern that deviates from the canonical auxin response and is necessary to sustain the expression of a subset of BRX-dependent auxin-responsive genes to drive root meristem growth. In the second part of this PhD thesis, we characterized the genome-wide impact of large scale deletions on four divergent Arabidopsis natural strains, through the integration of Ultra-High Throughput Sequencing data with data from genomic hybridizations on tiling arrays. Analysis of the identified deletions revealed a considerable portion of protein coding genes affected and supported a history of genomic rearrangements shaped by evolution. In the last part of the thesis, we showed that VIP3 gene in Arabidopsis has an evo-lutionary conserved role in the 3' to 5' mRNA degradation machinery, by applying a novel approach for the analysis of mRNA-Seq data from random-primed mRNA. Altogether, this PhD research contains major advancements in the study of natural genomic variation in plants and in the application of computational morphodynamics models for the functional characterization of biological pathways essential for the plant. - Récemment, l'introduction du séquençage de seconde génération et les avancées dans la microscopie confocale ont permis des études à l'échelle des différents systèmes cellulaires pour la caractérisation fonctionnelle de gènes. Le degrés de complexité intrinsèque à ces approches ont requis le développement de méthodologies bioinformatiques et de modèles mathématiques afin d'extraire de la masse de données expérimentale générée, des information biologiques significatives. Ce doctorat présente à la fois des méthodes bioinformatiques originales et des modèles mathématiques pour répondre à certaines questions spécifiques de Biologie Végétale en utilisant la plante Arabidopsis thaliana comme modèle. Premièrement, une analyse qualitative spatio-temporelle de profiles quantitatifs de transcripts et de protéines est utilisée pour montrer le rôle de la protéine BREVIS RADIX (BRX) dans le dialogue entre l'auxine et les cytokinines, des phytohormones, dans la croissance du méristème racinaire. Le noyau de ce travail de thèse est la caractérisation fonctionnelle de l'interaction entre la protéine BRX et la phytohormone auxine dans le méristème de la racine en utilisant des modèles informatiques basés sur des preuves expérimentales. Les hypothèses produites par le modèle ont mené à la découverte d'un schéma différentiel d'endocytose dans le méristème racinaire qui divise la réponse transcriptionnelle à l'auxine par le partitionnement de BRX de la membrane plasmique au noyau de la cellule. Cette information positionnelle crée une réponse transcriptionnelle à l'auxine qui dévie de la réponse canonique à l'auxine et est nécessaire pour soutenir l'expression d'un sous ensemble de gènes répondant à l'auxine et dépendant de BRX pour conduire la croissance du méristème. Dans la seconde partie de cette thèse de doctorat, nous avons caractérisé l'impact sur l'ensemble du génome des délétions à grande échelle sur quatre souches divergentes naturelles d'Arabidopsis, à travers l'intégration du séquençage à ultra-haut-débit avec l'hybridation génomique sur puces ADN. L'analyse des délétions identifiées a révélé qu'une proportion considérable de gènes codant était affectée, supportant l'idée d'un historique de réarrangement génomique modelé durant l'évolution. Dans la dernière partie de cette thèse, nous avons montré que le gène VÏP3 dans Arabidopsis a conservé un rôle évolutif dans la machinerie de dégradation des ARNm dans le sens 3' à 5', en appliquant une nouvelle approche pour l'analyse des données de séquençage d'ARNm issue de transcripts amplifiés aléatoirement. Dans son ensemble, cette recherche de doctorat contient des avancées majeures dans l'étude des variations génomiques naturelles des plantes et dans l'application de modèles morphodynamiques informatiques pour la caractérisation de réseaux biologiques essentiels à la plante. - Le développement des plantes est écrit dans leurs codes génétiques. Pour comprendre comment les plantes sont capables de s'adapter aux changements environnementaux, il est essentiel d'étudier comment leurs gènes gouvernent leur formation. Plus nous essayons de comprendre le fonctionnement d'une plante, plus nous réalisons la complexité des mécanismes biologiques, à tel point que l'utilisation d'outils et de modèles mathématiques devient indispensable. Dans ce travail, avec l'utilisation de la plante modèle Arabidopsis thalicinci nous avons résolu des problèmes biologiques spécifiques à travers le développement et l'application de méthodes informatiques concrètes. Dans un premier temps, nous avons investigué comment le gène BREVIS RADIX (BRX) régule le développement de la racine en contrôlant la réponse à deux hormones : l'auxine et la cytokinine. Nous avons employé une analyse statistique sur des mesures quantitatives de transcripts et de produits de gènes afin de démontrer que BRX joue un rôle antagonisant dans le dialogue entre ces deux hormones. Lorsque ce-dialogue moléculaire est perturbé, la racine primaire voit sa longueur dramatiquement réduite. Pour comprendre comment BRX répond à l'auxine, nous avons développé un modèle informatique basé sur des résultats expérimentaux. Les simulations successives ont mené à la découverte d'un signal positionnel qui contrôle la réponse de la racine à l'auxine par la régulation du mouvement intracellulaire de BRX. Dans la seconde partie de cette thèse, nous avons analysé le génome entier de quatre souches naturelles d'Arabidopsis et nous avons trouvé qu'une grande partie de leurs gènes étaient manquant par rapport à la souche de référence. Ce résultat indique que l'historique des modifications génomiques conduites par l'évolution détermine une disponibilité différentielle des gènes fonctionnels dans ces plantes. Dans la dernière partie de ce travail, nous avons analysé les données du transcriptome de la plante où le gène VIP3 était non fonctionnel. Ceci nous a permis de découvrir le rôle double de VIP3 dans la régulation de l'initiation de la transcription et dans la dégradation des transcripts. Ce rôle double n'avait jusqu'alors été démontrée que chez l'homme. Ce travail de doctorat supporte le développement et l'application de méthodologies informatiques comme outils inestimables pour résoudre la complexité des problèmes biologiques dans la recherche végétale. L'intégration de la biologie végétale et l'informatique est devenue de plus en plus importante pour l'avancée de nos connaissances sur le fonctionnement et le développement des plantes.

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MOTIVATION: Combinatorial interactions of transcription factors with cis-regulatory elements control the dynamic progression through successive cellular states and thus underpin all metazoan development. The construction of network models of cis-regulatory elements, therefore, has the potential to generate fundamental insights into cellular fate and differentiation. Haematopoiesis has long served as a model system to study mammalian differentiation, yet modelling based on experimentally informed cis-regulatory interactions has so far been restricted to pairs of interacting factors. Here, we have generated a Boolean network model based on detailed cis-regulatory functional data connecting 11 haematopoietic stem/progenitor cell (HSPC) regulator genes. RESULTS: Despite its apparent simplicity, the model exhibits surprisingly complex behaviour that we charted using strongly connected components and shortest-path analysis in its Boolean state space. This analysis of our model predicts that HSPCs display heterogeneous expression patterns and possess many intermediate states that can act as 'stepping stones' for the HSPC to achieve a final differentiated state. Importantly, an external perturbation or 'trigger' is required to exit the stem cell state, with distinct triggers characterizing maturation into the various different lineages. By focusing on intermediate states occurring during erythrocyte differentiation, from our model we predicted a novel negative regulation of Fli1 by Gata1, which we confirmed experimentally thus validating our model. In conclusion, we demonstrate that an advanced mammalian regulatory network model based on experimentally validated cis-regulatory interactions has allowed us to make novel, experimentally testable hypotheses about transcriptional mechanisms that control differentiation of mammalian stem cells. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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MOTIVATION: In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. RESULTS: In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. AVAILABILITY: The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

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BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.

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The opportunities and challenges for the study and control of parasitic diseases in the 21st century are both exciting and daunting. Based on the contributions from this field over the last part of the 20th century, we should expect new biologic concepts will continue to come from this discipline to enrich the general area of biomedical research. The general nature of such a broad category of infections is difficult to distill, but they often depend on well-orchestrated, complex life cycles and they often involve chronic, relatively well-balanced host/parasite relationships. Such characteristics force biological systems to their limits, and this may be why studies of these diseases have made fundamental contributions to molecular biology, cell biology and immunology. However, if these findings are to continue apace, parasitologists must capitalize on the new findings being generated though genomics, bioinformatics, proteomics, and genetic manipulations of both host and parasite. Furthermore, they must do so based on sound biological insights and the use of hypothesis-driven studies of these complex systems. A major challenge over the next century will be to capitalize on these new findings and translate them into successful, sustainable strategies for control, elimination and eradication of the parasitic diseases that pose major public health threats to the physical and cognitive development and health of so many people worldwide.

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ABSTRACT Malaria is a major worldwide public health problem, with transmission occurring throughout Africa, Asia, Oceania and Latin America. Over two billion people live in malarious areas of the world and it is estimated that 300-500 million cases and 1.5-2.7 million deaths occur annually. The increase in multi-drug resistant parasites and insecticide-resistant vectors has made the development of malaria vaccine a public health priority. The published genome offers tremendous opportunity for the identification of new antigens that can befast-tracked for vaccine development. We identified potential protein antigens present on the surface of asexual malaria blood stages through bioinformatics and published transcriptome and proteorné analysis. Amongst the proteins identified, we selected those that contain predicted a-helical coiled-coil regions, which are generally short and structurally stable as isolated fragments. Peptides were synthesized and used to immunize mice. Most peptides tested were immunogenic as demonstrated in ELISA assays, and induced antibodies of varying titres. In immunofluorescence assays, anti-sera from immunized mice reacted with native proteins expressed at different intraerythrocytic developmental stages of the parasite's cycle. In parallel in vitro ADCI functional studies, human antibodies affinity purified on some of these peptides inhibited parasite growth in association with monocytes in magnitudes similar to that seen in semiimmune African adults. Siudies using human immune sera taken from different malaria endemic regions, demonstrated that majority of peptides were recognized at high prevalence. 73 peptides were next tested in longitudinal studies in two cohorts separated in space and time in coastal Kenya. In these longitudinal analyses, antibody responses to peptides were sequentially examined in two cohorts of children at risk of clinical malaria in order to characterize the level of peptide recognition by age, and the role of anti-peptide antibodies in protection from clinical malaria. Ten peptides were associated ?with a significantly reduced odds ratio for an episode of clinical malaria in the first cohort of children and two of these peptides (LR146 and ÁS202.11) were associated with a significantly reduced odds ratio in both cohorts. This study has identified proteins PFB0145c and MAL6P1.37 among others as likely targets of protective antibodies. Our findings support further studies to systematically assess immunogenicity of peptides of interest in order to establish clear criteria for optimal design of potential vaccine constructs to be tested in clinical trials. RESUME La malaria est un problème de santé publique mondial principalement en Afrique, en Asie, en Océanie et en Amérique latine. Plus de 2 milliards de personnes vivent dans des régions endémiques et le nombre de cas par année est estimé entre 300 et 500 millions. 1.5 à 2.7 millions de décès surviennent annuellement dans ces zones. L'augmentation de la résistance aux médicaments et aux insecticides fait du développement d'un vaccin une priorité. Le séquençage complet du génome du parasite offre l'opportunité d'identifier de nouveaux antigènes qui peuvent rapidement mener au développement d'un vaccin. Des protéines antigéniques potentielles présentes à la surface des globules rouges infectés ont été identifiées par bioinformatique et par l'analyse du protéome et du transcriptome. Nous avons sélectionné, parmi ces protéines, celles contenant des motifs dits "a helical coiled-coil" qui sont généralement courts et structurellement stables. Ces régions ont été obtenues par synthèse peptidique et utilisées pour immuniser des souris. La plupart des peptides testés sont immunogéniques et induisent un titre variable d'anticorps déterminé par ELISA. Les résultats de tests d'immunofluorescence indiquent que les sera produits chez la souris reconnaissent les protéines natives exprimées aux différents stades de développement du parasite. En parallèle, des études d'ADCI in vitro montrent qué des anticorps humains purifiés à partir de ces peptides associés à des monocytes inhibent la croissance du parasite aussi bien que celle observée chez des adultes africains protégés. Des études d'antigénicité utilisant des sera de personnes protégées de différents âges vivant dans des régions endémiques montrent que la majorité des peptides sont reconnus avec une haute prévalence. 73 peptides ont été testés dans une étude longitudinale avec 2 cohortes de la côte du Kenya. Ces 2 groupes viennent de zones bien distinctes et les prélèvements n'ont pas été effectués pendant la même période. Dans cette étude, la réponse anticorps contre les peptides synthétiques a été testée dans les 2 cohortes d'enfants à risque de développer un épisode de malaria afin de caractériser le niveau de reconnaissance des peptides en fonction de l'âge et de déterminer le rôle des anticorps anti-peptides dans la protection contre la malaria. Parmi ces peptides, 10 sont associés à une réduction significative des risques de développer un épisode de malaria dans la première cohorte alors qu'un seul (LR146 et AS202.11) l'est dans les 2 cohortes. Cette étude a identifié, parmi d'autres, les protéines PFB0145c et MAL6P1.37 comme pouvant être la cible d'anticorps. Ces résultats sont en faveur de futures études qui évalueraient systématiquement l'immunogénicité des peptides d'intérêt dans le but d'établir des critères de sélection clairs pour le développement d'un vaccin. Résumé pour un large public La malaria est un problème de santé publique mondial principalement en Afrique, en Asie, en Océanie et en Amérique latine. Plus de 2 milliards de personnes vivent dans des régions endémiques et le nombre de cas par année est estimé entre 300 et 500 millions. 1.5 à 2.7 millions de décès surviennent annuellement dans ces zones. La résistance aux médicaments et aux insecticides augmente de plus en plus d'où la nécessité de développer un vaccin. Le séquençage complet du génome (ensemble des gènes) de P. falciparum a conduit au développement de nouvelles .études à large échelle dans le domaine des protéines du parasite (protéome) ; dans l'utilisation d'algorithmes, de techniques informatiques et statistiques pour l'analyse de données biologiques (bioinformatique) et dans les technologies de transcription et de profiles d'expression (transcriptome). Nous avons identifié, en utilisant les outils ci-dessus, des nouvelles protéines antigéniques qui sont présentes au stade sanguin de la malaria. Nous avons sélectionné, parmi ces protéines, celles contenant un motif dit "a-helical coiled-coil" qui sont des domaines impliqués dans un large éventail de fonctions biologiques. Des peptides représentant ces régions structurellement stables ont été synthétisés et utilisés pour immuniser des souris. La plupart des peptides testés sont immunogéniques et induisent un titre variable d'anticorps déterminé par ELISA. Les résultats de tests d'immunofluorescence indiquent que plusieurs sera de souris immunisées avec ces peptides reconnaissent les protéines natives exprimées à la surface des globules rouges infectés. En parallèle, des études d'ADCI in vitro montrent que des anticorps humains purifiés à partir de ces peptides en présence de monocytes inhibent la croissance du parasite de manière similaire à celle observée chez des adultes africains protégés. Des études d'antigénicité utilisant des sera de personnes immunes de différents âges (adultes et enfants) vivant dans des régions endémiques montrent que la majorité des peptides sont reconnus avec une haute prévalence. 73 peptides ont été testés dans des études épidémiologiques dans 2 villages côtiers du Kenya Ces 2 groupes vivent dans des zones bien distinctes et les prélèvements n'ont pas été effectués pendant la même période. Dans ces études, la réponse anticorps dirigée contre les peptides synthétiques a été testée en utilisant 467 échantillons sanguins d'enfants à risque de développer un épisode de malaria afin de caractériser le niveau de reconnaissance des peptides en fonction de l'âge et de déterminer le rôle des anticorps anti-peptides dans la protection contre la malaria cérébrale. Parmi ces peptides, 10 sont associés à une protection contre un épisode de malaria dans le premier village alors qu'un seul l'est dans les 2 villages. Ces résultats sont en faveur de futures études qui évalueraient systématiquement l'immunogénicité des peptides intéressants dans le but d'établir des critères de sélection clairs pour le développement d'un vaccin.

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BACKGROUND: DNA sequence integrity, mRNA concentrations and protein-DNA interactions have been subject to genome-wide analyses based on microarrays with ever increasing efficiency and reliability over the past fifteen years. However, very recently novel technologies for Ultra High-Throughput DNA Sequencing (UHTS) have been harnessed to study these phenomena with unprecedented precision. As a consequence, the extensive bioinformatics environment available for array data management, analysis, interpretation and publication must be extended to include these novel sequencing data types. DESCRIPTION: MIMAS was originally conceived as a simple, convenient and local Microarray Information Management and Annotation System focused on GeneChips for expression profiling studies. MIMAS 3.0 enables users to manage data from high-density oligonucleotide SNP Chips, expression arrays (both 3'UTR and tiling) and promoter arrays, BeadArrays as well as UHTS data using MIAME-compliant standardized vocabulary. Importantly, researchers can export data in MAGE-TAB format and upload them to the EBI's ArrayExpress certified data repository using a one-step procedure. CONCLUSION: We have vastly extended the capability of the system such that it processes the data output of six types of GeneChips (Affymetrix), two different BeadArrays for mRNA and miRNA (Illumina) and the Genome Analyzer (a popular Ultra-High Throughput DNA Sequencer, Illumina), without compromising on its flexibility and user-friendliness. MIMAS, appropriately renamed into Multiomics Information Management and Annotation System, is currently used by scientists working in approximately 50 academic laboratories and genomics platforms in Switzerland and France. MIMAS 3.0 is freely available via http://multiomics.sourceforge.net/.

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The MyHits web server (http://myhits.isb-sib.ch) is a new integrated service dedicated to the annotation of protein sequences and to the analysis of their domains and signatures. Guest users can use the system anonymously, with full access to (i) standard bioinformatics programs (e.g. PSI-BLAST, ClustalW, T-Coffee, Jalview); (ii) a large number of protein sequence databases, including standard (Swiss-Prot, TrEMBL) and locally developed databases (splice variants); (iii) databases of protein motifs (Prosite, Interpro); (iv) a precomputed list of matches ('hits') between the sequence and motif databases. All databases are updated on a weekly basis and the hit list is kept up to date incrementally. The MyHits server also includes a new collection of tools to generate graphical representations of pairwise and multiple sequence alignments including their annotated features. Free registration enables users to upload their own sequences and motifs to private databases. These are then made available through the same web interface and the same set of analytical tools. Registered users can manage their own sequences and annotations using only web tools and freeze their data in their private database for publication purposes.

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The great expansion in the number of genome sequencing projects has revealed the importance of computational methods to speed up the characterization of unknown genes. These studies have been improved by the use of three dimensional information from the predicted proteins generated by molecular modeling techniques. In this work, we disclose the structure-function relationship of a gene product from Leishmania amazonensis by applying molecular modeling and bioinformatics techniques. The analyzed sequence encodes a 159 aminoacids polypeptide (estimated 18 kDa) and was denoted LaPABP for its high homology with poly-A binding proteins from trypanosomatids. The domain structure, clustering analysis and a three dimensional model of LaPABP, basically obtained by homology modeling on the structure of the human poly-A binding protein, are described. Based on the analysis of the electrostatic potential mapped on the model's surface and conservation of intramolecular contacts responsible for folding stabilization we hypothesize that this protein may have less avidity to RNA than it's L. major counterpart but still account for a significant functional activity in the parasite. The model obtained will help in the design of mutagenesis experiments aimed to elucidate the mechanism of gene expression in trypanosomatids and serve as a starting point for its exploration as a potential source of targets for a rational chemotherapy.

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Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot

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The study of the Schistosoma mansoni genome, one of the etiologic agents of human schistosomiasis, is essential for a better understanding of the biology and development of this parasite. In order to get an overview of all S. mansoni catalogued gene sequences, we performed a clustering analysis of the parasite mRNA sequences available in public databases. This was made using softwares PHRAP and CAP3. The consensus sequences, generated after the alignment of cluster constituent sequences, allowed the identification by database homology searches of the most expressed genes in the worm. We analyzed these genes and looked for a correlation between their high expression and parasite metabolism and biology. We observed that the majority of these genes is related to the maintenance of basic cell functions, encoding genes whose products are related to the cytoskeleton, intracellular transport and energy metabolism. Evidences are presented here that genes for aerobic energy metabolism are expressed in all the developmental stages analyzed. Some of the most expressed genes could not be identified by homology searches and may have some specific functions in the parasite.