201 research outputs found

    Туризм як форма транскордонного співробітництва Карпатського Єврорегіону. (Tourism as a form of cross-border cooperation of the Carpathian European region.)

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    Карпатський єврорегіон – це перша транскордонна організація, створена на території України. Володіючи значним природним, рекреаційним та історико-культурним потенціалом туризм виходить на одне з перших місць у співпраці країн. (Tourism as a form of cross-border cooperation in the Carpathian Euroregion. Carpathian Euroregion is the first crossborder organization founded in Ukraine. Endowed with significant natural, recreational, historical and cultural tourism potential goes to one of the first places in the cooperation countries.

    Recommendations to the formulation of EU regulation 2092/91 on livestock production

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    Within the SAFO network, the workpackage on standard development has focussed on the topic, on how and to what degree the EU-Regulations con-tribute to the objective of a high status of anima health and food safety in organic livestock production. Results and conclusions from the discussions at 5 SAFO workshops are presented

    Uncertain groupings: probabilistic combination of grouping data

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    Probabilistic approaches for data integration have much potential. We view data integration as an iterative process where data understanding gradually increases as the data scientist continuously refines his view on how to deal with learned intricacies like data conflicts. This paper presents a probabilistic approach for integrating data on groupings. We focus on a bio-informatics use case concerning homology. A bio-informatician has a large number of homology data sources to choose from. To enable querying combined knowledge contained in these sources, they need to be integrated. We validate our approach by integrating three real-world biological databases on homology in three iterations

    PCV26: HOW MUCH DOES ONE GRAM OF HUMAN HEART MUSCLE COST?

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    ProGMap: an integrated annotation resource for protein orthology

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    Current protein sequence databases employ different classification schemes that often provide conflicting annotations, especially for poorly characterized proteins. ProGMap (Protein Group Mappings, http://www.bioinformatics.nl/progmap) is a web-tool designed to help researchers and database annotators to assess the coherence of protein groups defined in various databases and thereby facilitate the annotation of newly sequenced proteins. ProGMap is based on a non-redundant dataset of over 6.6 million protein sequences which is mapped to 240 000 protein group descriptions collected from UniProt, RefSeq, Ensembl, COG, KOG, OrthoMCL-DB, HomoloGene, TRIBES and PIRSF. ProGMap combines the underlying classification schemes via a network of links constructed by a fast and fully automated mapping approach originally developed for document classification. The web interface enables queries to be made using sequence identifiers, gene symbols, protein functions or amino acid and nucleotide sequences. For the latter query type BLAST similarity search and QuickMatch identity search services have been incorporated, for finding sequences similar (or identical) to a query sequence. ProGMap is meant to help users of high throughput methodologies who deal with partially annotated genomic data

    Multi-netclust: an efficient tool for finding connected clusters in multi-parametric networks

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    Summary: Multi-netclust is a simple tool that allows users to extract connected clusters of data represented by different networks given in the form of matrices. The tool uses user-defined threshold values to combine the matrices, and uses a straightforward, memory-efficient graph algorithm to find clusters that are connected in all or in either of the networks. The tool is written in C/C++ and is available either as a form-based or as a command-line-based program running on Linux platforms. The algorithm is fast, processing a network of > 106 nodes and 108 edges takes only a few minutes on an ordinary computer

    PLATFORM policy brief No. 3. The role of the ERA-NET instrument in fostering inclusiveness

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    In the spirit of building an inclusive European Research Area, this policy brief provides recommendations for the European Commission (EC), ERA -NET initiatives and the so -called lower performing countries (LPCs) on how LPCs can become an integral and emp owered part of the ERA -NET community

    Interoperability and FAIRness through a novel combination of Web technologies

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    Data in the life sciences are extremely diverse and are stored in a broad spectrum of repositories ranging from those designed for particular data types (such as KEGG for pathway data or UniProt for protein data) to those that are general-purpose (such as FigShare, Zenodo, Dataverse or EUDAT). These data have widely different levels of sensitivity and security considerations. For example, clinical observations about genetic mutations in patients are highly sensitive, while observations of species diversity are generally not. The lack of uniformity in data models from one repository to another, and in the richness and availability of metadata descriptions, makes integration and analysis of these data a manual, time-consuming task with no scalability. Here we explore a set of resource-oriented Web design patterns for data discovery, accessibility, transformation, and integration that can be implemented by any general- or special-purpose repository as a means to assist users in finding and reusing their data holdings. We show that by using off-the-shelf technologies, interoperability can be achieved atthe level of an individual spreadsheet cell. We note that the behaviours of this architecture compare favourably to the desiderata defined by the FAIR Data Principles, and can therefore represent an exemplar implementation of those principles. The proposed interoperability design patterns may be used to improve discovery and integration of both new and legacy data, maximizing the utility of all scholarly outputs

    DODO: an efficient orthologous genes assignment tool based on domain architectures. Domain based ortholog detection

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    <p>Abstract</p> <p>Background</p> <p>Orthologs are genes derived from the same ancestor gene loci after speciation events. Orthologous proteins usually have similar sequences and perform comparable biological functions. Therefore, ortholog identification is useful in annotations of newly sequenced genomes. With rapidly increasing number of sequenced genomes, constructing or updating ortholog relationship between all genomes requires lots of effort and computation time. In addition, elucidating ortholog relationships between distantly related genomes is challenging because of the lower sequence similarity. Therefore, an efficient ortholog detection method that can deal with large number of distantly related genomes is desired.</p> <p>Results</p> <p>An efficient ortholog detection pipeline DODO (DOmain based Detection of Orthologs) is created on the basis of domain architectures in this study. Supported by domain composition, which usually directly related with protein function, DODO could facilitate orthologs detection across distantly related genomes. DODO works in two main steps. Starting from domain information, it first assigns protein groups according to their domain architectures and further identifies orthologs within those groups with much reduced complexity. Here DODO is shown to detect orthologs between two genomes in considerably shorter period of time than traditional methods of reciprocal best hits and it is more significant when analyzed a large number of genomes. The output results of DODO are highly comparable with other known ortholog databases.</p> <p>Conclusions</p> <p>DODO provides a new efficient pipeline for detection of orthologs in a large number of genomes. In addition, a database established with DODO is also easier to maintain and could be updated relatively effortlessly. The pipeline of DODO could be downloaded from <url>http://140.109.42.19:16080/dodo_web/home.htm</url></p
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