966 resultados para Database search


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We present and validate BlastR, a method for efficiently and accurately searching non-coding RNAs. Our approach relies on the comparison of di-nucleotides using BlosumR, a new log-odd substitution matrix. In order to use BlosumR for comparison, we recoded RNA sequences into protein-like sequences. We then showed that BlosumR can be used along with the BlastP algorithm in order to search non-coding RNA sequences. Using Rfam as a gold standard, we benchmarked this approach and show BlastR to be more sensitive than BlastN. We also show that BlastR is both faster and more sensitive than BlastP used with a single nucleotide log-odd substitution matrix. BlastR, when used in combination with WU-BlastP, is about 5% more accurate than WU-BlastN and about 50 times slower. The approach shown here is equally effective when combined with the NCBI-Blast package. The software is an open source freeware available from www.tcoffee.org/blastr.html.

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The Eukaryotic Promoter Database (EPD) is an annotated non-redundant collection of eukaryotic POL II promoters, experimentally defined by a transcription start site (TSS). There may be multiple promoter entries for a single gene. The underlying experimental evidence comes from journal articles and, starting from release 73, from 5' ESTs of full-length cDNA clones used for so-called in silico primer extension. Access to promoter sequences is provided by pointers to TSS positions in nucleotide sequence entries. The annotation part of an EPD entry includes a description of the type and source of the initiation site mapping data, links to other biological databases and bibliographic references. EPD is structured in a way that facilitates dynamic extraction of biologically meaningful promoter subsets for comparative sequence analysis. Web-based interfaces have been developed that enable the user to view EPD entries in different formats, to select and extract promoter sequences according to a variety of criteria and to navigate to related databases exploiting different cross-references. Tools for analysing sequence motifs around TSSs defined in EPD are provided by the signal search analysis server. EPD can be accessed at http://www.epd. isb-sib.ch.

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The InterPro database (http://www.ebi.ac.uk/interpro/) is a freely available resource that can be used to classify sequences into protein families and to predict the presence of important domains and sites. Central to the InterPro database are predictive models, known as signatures, from a range of different protein family databases that have different biological focuses and use different methodological approaches to classify protein families and domains. InterPro integrates these signatures, capitalizing on the respective strengths of the individual databases, to produce a powerful protein classification resource. Here, we report on the status of InterPro as it enters its 15th year of operation, and give an overview of new developments with the database and its associated Web interfaces and software. In particular, the new domain architecture search tool is described and the process of mapping of Gene Ontology terms to InterPro is outlined. We also discuss the challenges faced by the resource given the explosive growth in sequence data in recent years. InterPro (version 48.0) contains 36 766 member database signatures integrated into 26 238 InterPro entries, an increase of over 3993 entries (5081 signatures), since 2012.

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Résumé: L'automatisation du séquençage et de l'annotation des génomes, ainsi que l'application à large échelle de méthodes de mesure de l'expression génique, génèrent une quantité phénoménale de données pour des organismes modèles tels que l'homme ou la souris. Dans ce déluge de données, il devient très difficile d'obtenir des informations spécifiques à un organisme ou à un gène, et une telle recherche aboutit fréquemment à des réponses fragmentées, voir incomplètes. La création d'une base de données capable de gérer et d'intégrer aussi bien les données génomiques que les données transcriptomiques peut grandement améliorer la vitesse de recherche ainsi que la qualité des résultats obtenus, en permettant une comparaison directe de mesures d'expression des gènes provenant d'expériences réalisées grâce à des techniques différentes. L'objectif principal de ce projet, appelé CleanEx, est de fournir un accès direct aux données d'expression publiques par le biais de noms de gènes officiels, et de représenter des données d'expression produites selon des protocoles différents de manière à faciliter une analyse générale et une comparaison entre plusieurs jeux de données. Une mise à jour cohérente et régulière de la nomenclature des gènes est assurée en associant chaque expérience d'expression de gène à un identificateur permanent de la séquence-cible, donnant une description physique de la population d'ARN visée par l'expérience. Ces identificateurs sont ensuite associés à intervalles réguliers aux catalogues, en constante évolution, des gènes d'organismes modèles. Cette procédure automatique de traçage se fonde en partie sur des ressources externes d'information génomique, telles que UniGene et RefSeq. La partie centrale de CleanEx consiste en un index de gènes établi de manière hebdomadaire et qui contient les liens à toutes les données publiques d'expression déjà incorporées au système. En outre, la base de données des séquences-cible fournit un lien sur le gène correspondant ainsi qu'un contrôle de qualité de ce lien pour différents types de ressources expérimentales, telles que des clones ou des sondes Affymetrix. Le système de recherche en ligne de CleanEx offre un accès aux entrées individuelles ainsi qu'à des outils d'analyse croisée de jeux de donnnées. Ces outils se sont avérés très efficaces dans le cadre de la comparaison de l'expression de gènes, ainsi que, dans une certaine mesure, dans la détection d'une variation de cette expression liée au phénomène d'épissage alternatif. Les fichiers et les outils de CleanEx sont accessibles en ligne (http://www.cleanex.isb-sib.ch/). Abstract: The automatic genome sequencing and annotation, as well as the large-scale gene expression measurements methods, generate a massive amount of data for model organisms. Searching for genespecific or organism-specific information througout all the different databases has become a very difficult task, and often results in fragmented and unrelated answers. The generation of a database which will federate and integrate genomic and transcriptomic data together will greatly improve the search speed as well as the quality of the results by allowing a direct comparison of expression results obtained by different techniques. The main goal of this project, called the CleanEx database, is thus to provide access to public gene expression data via unique gene names and to represent heterogeneous expression data produced by different technologies in a way that facilitates joint analysis and crossdataset comparisons. A consistent and uptodate gene nomenclature is achieved by associating each single gene expression experiment with a permanent target identifier consisting of a physical description of the targeted RNA population or the hybridization reagent used. These targets are then mapped at regular intervals to the growing and evolving catalogues of genes from model organisms, such as human and mouse. The completely automatic mapping procedure relies partly on external genome information resources such as UniGene and RefSeq. The central part of CleanEx is a weekly built gene index containing crossreferences to all public expression data already incorporated into the system. In addition, the expression target database of CleanEx provides gene mapping and quality control information for various types of experimental resources, such as cDNA clones or Affymetrix probe sets. The Affymetrix mapping files are accessible as text files, for further use in external applications, and as individual entries, via the webbased interfaces . The CleanEx webbased query interfaces offer access to individual entries via text string searches or quantitative expression criteria, as well as crossdataset analysis tools, and crosschip gene comparison. These tools have proven to be very efficient in expression data comparison and even, to a certain extent, in detection of differentially expressed splice variants. The CleanEx flat files and tools are available online at: http://www.cleanex.isbsib. ch/.

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Quest for Orthologs (QfO) is a community effort with the goal to improve and benchmark orthology predictions. As quality assessment assumes prior knowledge on species phylogenies, we investigated the congruency between existing species trees by comparing the relationships of 147 QfO reference organisms from six Tree of Life (ToL)/species tree projects: The National Center for Biotechnology Information (NCBI) taxonomy, Opentree of Life, the sequenced species/species ToL, the 16S ribosomal RNA (rRNA) database, and trees published by Ciccarelli et al. (Ciccarelli FD, et al. 2006. Toward automatic reconstruction of a highly resolved tree of life. Science 311:1283-1287) and by Huerta-Cepas et al. (Huerta-Cepas J, Marcet-Houben M, Gabaldon T. 2014. A nested phylogenetic reconstruction approach provides scalable resolution in the eukaryotic Tree Of Life. PeerJ PrePrints 2:223) Our study reveals that each species tree suggests a different phylogeny: 87 of the 146 (60%) possible splits of a dichotomous and rooted tree are congruent, while all other splits are incongruent in at least one of the species trees. Topological differences are observed not only at deep speciation events, but also within younger clades, such as Hominidae, Rodentia, Laurasiatheria, or rosids. The evolutionary relationships of 27 archaea and bacteria are highly inconsistent. By assessing 458,108 gene trees from 65 genomes, we show that consistent species topologies are more often supported by gene phylogenies than contradicting ones. The largest concordant species tree includes 77 of the QfO reference organisms at the most. Results are summarized in the form of a consensus ToL (http://swisstree.vital-it.ch/species_tree) that can serve different benchmarking purposes.

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Current-day web search engines (e.g., Google) do not crawl and index a significant portion of theWeb and, hence, web users relying on search engines only are unable to discover and access a large amount of information from the non-indexable part of the Web. Specifically, dynamic pages generated based on parameters provided by a user via web search forms (or search interfaces) are not indexed by search engines and cannot be found in searchers’ results. Such search interfaces provide web users with an online access to myriads of databases on the Web. In order to obtain some information from a web database of interest, a user issues his/her query by specifying query terms in a search form and receives the query results, a set of dynamic pages that embed required information from a database. At the same time, issuing a query via an arbitrary search interface is an extremely complex task for any kind of automatic agents including web crawlers, which, at least up to the present day, do not even attempt to pass through web forms on a large scale. In this thesis, our primary and key object of study is a huge portion of the Web (hereafter referred as the deep Web) hidden behind web search interfaces. We concentrate on three classes of problems around the deep Web: characterization of deep Web, finding and classifying deep web resources, and querying web databases. Characterizing deep Web: Though the term deep Web was coined in 2000, which is sufficiently long ago for any web-related concept/technology, we still do not know many important characteristics of the deep Web. Another matter of concern is that surveys of the deep Web existing so far are predominantly based on study of deep web sites in English. One can then expect that findings from these surveys may be biased, especially owing to a steady increase in non-English web content. In this way, surveying of national segments of the deep Web is of interest not only to national communities but to the whole web community as well. In this thesis, we propose two new methods for estimating the main parameters of deep Web. We use the suggested methods to estimate the scale of one specific national segment of the Web and report our findings. We also build and make publicly available a dataset describing more than 200 web databases from the national segment of the Web. Finding deep web resources: The deep Web has been growing at a very fast pace. It has been estimated that there are hundred thousands of deep web sites. Due to the huge volume of information in the deep Web, there has been a significant interest to approaches that allow users and computer applications to leverage this information. Most approaches assumed that search interfaces to web databases of interest are already discovered and known to query systems. However, such assumptions do not hold true mostly because of the large scale of the deep Web – indeed, for any given domain of interest there are too many web databases with relevant content. Thus, the ability to locate search interfaces to web databases becomes a key requirement for any application accessing the deep Web. In this thesis, we describe the architecture of the I-Crawler, a system for finding and classifying search interfaces. Specifically, the I-Crawler is intentionally designed to be used in deepWeb characterization studies and for constructing directories of deep web resources. Unlike almost all other approaches to the deep Web existing so far, the I-Crawler is able to recognize and analyze JavaScript-rich and non-HTML searchable forms. Querying web databases: Retrieving information by filling out web search forms is a typical task for a web user. This is all the more so as interfaces of conventional search engines are also web forms. At present, a user needs to manually provide input values to search interfaces and then extract required data from the pages with results. The manual filling out forms is not feasible and cumbersome in cases of complex queries but such kind of queries are essential for many web searches especially in the area of e-commerce. In this way, the automation of querying and retrieving data behind search interfaces is desirable and essential for such tasks as building domain-independent deep web crawlers and automated web agents, searching for domain-specific information (vertical search engines), and for extraction and integration of information from various deep web resources. We present a data model for representing search interfaces and discuss techniques for extracting field labels, client-side scripts and structured data from HTML pages. We also describe a representation of result pages and discuss how to extract and store results of form queries. Besides, we present a user-friendly and expressive form query language that allows one to retrieve information behind search interfaces and extract useful data from the result pages based on specified conditions. We implement a prototype system for querying web databases and describe its architecture and components design.

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The theoretical research of the study concentrated on finding theoretical frameworks to optimize the amount of needed stock keeping units (SKUs) in manufacturing industry. The goal was to find ways for a company to acquire an optimal collection of stock keeping units needed for manufacturing needed amount of end products. The research follows constructive research approach leaning towards practical problem solving. In the empirical part of this study, a recipe search tool was developed to an existing database used in the target company. The purpose of the tools was to find all the recipes meeting the EUPS performance standard and put the recipes in a ranking order using the data available in the database. The ranking of the recipes was formed from the combination of the performance measures and price of the recipes. In addition, the tool researched what kind of paper SKUs were needed to manufacture the best performing recipes. The tool developed during this process meets the requirements. It eases and makes it much faster to search for all the recipes meeting the EUPS standard. Furthermore, many future development possibilities for the tool were discovered while writing the thesis.

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This 2-page planner will help students search databases more effectively using Boolean logic

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Thirty one new sodium heterosulfamates, RNHSO3Na, where the R portion contains mainly thiazole, benzothiazole, thiadiazole and pyridine ring structures, have been synthesized and their taste portfolios have been assessed. A database of 132 heterosulfamates ( both open-chain and cyclic) has been formed by combining these new compounds with an existing set of 101 heterosulfamates which were previously synthesized and for which taste data are available. Simple descriptors have been obtained using (i) measurements with Corey-Pauling-Koltun (CPK) space- filling models giving x, y and z dimensions and a volume VCPK, (ii) calculated first order molecular connectivities ((1)chi(v)) and (iii) the calculated Spartan program parameters to obtain HOMO, LUMO energies, the solvation energy E-solv and V-SPART AN. The techniques of linear (LDA) and quadratic (QDA) discriminant analysis and Tree analysis have then been employed to develop structure-taste relationships (SARs) that classify the sweet (S) and non-sweet (N) compounds into separate categories. In the LDA analysis 70% of the compounds were correctly classified ( this compares with 65% when the smaller data set of 101 compounds was used) and in the QDA analysis 68% were correctly classified ( compared to 80% previously). TheTree analysis correctly classified 81% ( compared to 86% previously). An alternative Tree analysis derived using the Cerius2 program and a set of physicochemical descriptors correctly classified only 54% of the compounds.

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We introduce a classification-based approach to finding occluding texture boundaries. The classifier is composed of a set of weak learners, which operate on image intensity discriminative features that are defined on small patches and are fast to compute. A database that is designed to simulate digitized occluding contours of textured objects in natural images is used to train the weak learners. The trained classifier score is then used to obtain a probabilistic model for the presence of texture transitions, which can readily be used for line search texture boundary detection in the direction normal to an initial boundary estimate. This method is fast and therefore suitable for real-time and interactive applications. It works as a robust estimator, which requires a ribbon-like search region and can handle complex texture structures without requiring a large number of observations. We demonstrate results both in the context of interactive 2D delineation and of fast 3D tracking and compare its performance with other existing methods for line search boundary detection.

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Some unexpected promiscuous inhibitors were observed in a virtual screening protocol applied to select cruzain inhibitors from the ZINC database. Physical-chemical and pharmacophore model filters were used to reduce the database size. The selected compounds were docked into the cruzain active site. Six hit compounds were tested as inhibitors. Although the compounds were designed to be nucleophilically attacked by the catalytic cysteine of cruzain, three of them showed typical promiscuous behavior, revealing that false positives are a prevalent concern in VS programs. (C) 2007 Elsevier Ltd. All rights reserved.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The main goal of our research was to search for SSRs in the Eucalyptus EST FORESTs database (using a software for mining SSR-motifs). With this objective, we created a database for cataloging Eucalyptus EST-derived SSRs, and developed a bioinformatics tool, named Satellyptus, for finding and analyzing microsatellites in the Eucalyptus EST database. The search for microsatellites in the FORESTs database containing 71,115 Eucalyptus EST sequences (52.09 Mb) revealed 20,530 SSRs in 15,621 ESTs. The SSR abundance detected on the Eucalyptus ESTs database (29% or one microsatellite every four sequences) is considered very high for plants. Amongst the categories of SSR motifs, the dimeric (37%) and trimeric ones (33%) predominated. The AG/CT motif was the most frequent (35.15%) followed by the trimeric CCG/CGG (12.81%). From a random sample of 1,217 sequences, 343 microsatellites in 265 SSR-containing sequences were identified. Approximately 48% of these ESTs containing microsatellites were homologous to proteins with known biological function. Most of the microsatellites detected in Eucalyptus ESTs were positioned at either the 5 or 3 end. Our next priority involves the design of flanking primers for codominant SSR loci, which could lead to the development of a set of microsatellite-based markers suitable for marker-assisted Eucalyptus breeding programs.

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Tick-borne zoonoses (TBZ) are emerging diseases worldwide. A large amount of information (e.g. case reports, results of epidemiological surveillance, etc.) is dispersed through various reference sources (ISI and non-ISI journals, conference proceedings, technical reports, etc.). An integrated database-derived from the ICTTD-3 project (http://www.icttd.nl)-was developed in order to gather TBZ records in the (sub-)tropics, collected both by the authors and collaborators worldwide. A dedicated website (http://www.tickbornezoonoses.org) was created to promote collaboration and circulate information. Data collected are made freely available to researchers for analysis by spatial methods, integrating mapped ecological factors for predicting TBZ risk. The authors present the assembly process of the TBZ database: the compilation of an updated list of TBZ relevant for (sub-)tropics, the database design and its structure, the method of bibliographic search, the assessment of spatial precision of geo-referenced records. At the time of writing, 725 records extracted from 337 publications related to 59 countries in the (sub-)tropics, have been entered in the database. TBZ distribution maps were also produced. Imported cases have been also accounted for. The most important datasets with geo-referenced records were those on Spotted Fever Group rickettsiosis in Latin-America and Crimean-Congo Haemorrhagic Fever in Africa. The authors stress the need for international collaboration in data collection to update and improve the database. Supervision of data entered remains always necessary. Means to foster collaboration are discussed. The paper is also intended to describe the challenges encountered to assemble spatial data from various sources and to help develop similar data collections.

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DBMODELING is a relational database of annotated comparative protein structure models and their metabolic, pathway characterization. It is focused on enzymes identified in the genomes of Mycobacterium tuberculosis and Xylella fastidiosa. The main goal of the present database is to provide structural models to be used in docking simulations and drug design. However, since the accuracy of structural models is highly dependent on sequence identity between template and target, it is necessary to make clear to the user that only models which show high structural quality should be used in such efforts. Molecular modeling of these genomes generated a database, in which all structural models were built using alignments presenting more than 30% of sequence identity, generating models with medium and high accuracy. All models in the database are publicly accessible at http://www.biocristalografia.df.ibilce.unesp.br/tools. DBMODELING user interface provides users friendly menus, so that all information can be printed in one stop from any web browser. Furthermore, DBMODELING also provides a docking interface, which allows the user to carry out geometric docking simulation, against the molecular models available in the database. There are three other important homology model databases: MODBASE, SWISSMODEL, and GTOP. The main applications of these databases are described in the present article. © 2007 Bentham Science Publishers Ltd.