Mining semantic networks of bioinformatics e-resources from the literature

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    Abstract

    There have been a number of recent efforts (e.g. BioCatalogue, BioMOBY, etc.) to systematically catalogue bioinformatics tools, services and datasets. These efforts mostly rely on manual curation and are unable to cope with the huge influx of various electronic resources, which consequently result in their unavailability to the community. We present a text mining approach that utilizes the literature to extract and semantically profile bioinformatics resources. Our method identifies the mentions of resources in the literature and assigns a set of co-occurring terminological and ontological entities (descriptors) to represent them. Since such representations can be extremely sparse, we use kernel metrics based on lexical term/descriptor similarities to identify semantically related resources. Resources are then either clustered or linked into a network, providing the users (bioinformaticians and service/tool crawlers) with a possibility to explore tools, services and datasets based on their relatedness, thus potentially improving the resource discovery process.
    Original languageEnglish
    Title of host publicationCEUR Workshop Proceedings|CEUR Workshop Proc.
    PublisherRWTH Aachen University
    Volume559
    Publication statusPublished - 2009
    EventWorkshop on Semantic Web Applications and Tools for Life Sciences, SWAT4LS 2009 - Amsterdam
    Duration: 1 Jul 2009 → …

    Publication series

    NameCEUR Workshop Proceedings

    Conference

    ConferenceWorkshop on Semantic Web Applications and Tools for Life Sciences, SWAT4LS 2009
    CityAmsterdam
    Period1/07/09 → …

    Keywords

    • Bioinformatics services
    • Kernel similarity
    • Networks
    • Service description
    • Text mining

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