IDPredictor : predict database links in biomedical database

Lade...
Vorschaubild
Dateien
Mehlhorn_0-396389.pdf
Mehlhorn_0-396389.pdfGröße: 735.9 KBDownloads: 237
Datum
2012
Autor:innen
Mehlhorn, Hendrik
Lange, Matthias
Scholz, Uwe
Herausgeber:innen
Kontakt
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
ArXiv-ID
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Open Access Green
Core Facility der Universität Konstanz
Gesperrt bis
Titel in einer weiteren Sprache
Forschungsvorhaben
Organisationseinheiten
Zeitschriftenheft
Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published
Erschienen in
Journal of Integrative Bioinformatics - JIB ; 9,2. 2012, 190. eISSN 1613-4516. Available under: doi: 10.2390/biecoll-jib-2012-190
Zusammenfassung

Knowledge found in biomedical databases, in particular in Web information systems, is a major bioinformatics resource. In general, this biological knowledge is worldwide represented in a network of databases. These data is spread among thousands of databases, which overlap in content, but differ substantially with respect to content detail, interface, formats and data structure. To support a functional annotation of lab data, such as protein sequences, metabolites or DNA sequences as well as a semi-automated data exploration in information retrieval environments, an integrated view to databases is essential. Search engines have the potential of assisting in data retrieval from these structured sources, but fall short of providing a comprehensive knowledge except out of the interlinked databases. A prerequisite of supporting the concept of an integrated data view is to acquire insights into cross-references among database entities. This issue is being hampered by the fact, that only a fraction of all possible cross-references are explicitely tagged in the particular biomedical informations systems. In this work, we investigate to what extend an automated construction of an integrated data network is possible. We propose a method that predicts and extracts cross-references from multiple life science databases and possible referenced data targets. We study the retrieval quality of our method and report on first, promising results. The method is implemented as the tool IDPredictor, which is published under the DOI 10.5447/IPK/2012/4 and is freely available using the URL: http://dx.doi.org/10.5447/IPK/2012/4.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Data processing, computer science, computer systems
Konferenz
International Symposium on Integrative Bioinformatics, 2. Apr. 2012 - 4. Apr. 2012, Hangzhou, China
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690MEHLHORN, Hendrik, Matthias LANGE, Uwe SCHOLZ, Falk SCHREIBER, 2012. IDPredictor : predict database links in biomedical database. International Symposium on Integrative Bioinformatics. Hangzhou, China, 2. Apr. 2012 - 4. Apr. 2012. In: Journal of Integrative Bioinformatics - JIB ; 9,2. 2012, 190. eISSN 1613-4516. Available under: doi: 10.2390/biecoll-jib-2012-190
BibTex
@inproceedings{Mehlhorn2012-06-26IDPre-38616,
  year={2012},
  doi={10.2390/biecoll-jib-2012-190},
  title={IDPredictor : predict database links in biomedical database},
  booktitle={Journal of Integrative Bioinformatics - JIB ; 9,2},
  author={Mehlhorn, Hendrik and Lange, Matthias and Scholz, Uwe and Schreiber, Falk},
  note={Article Number: 190}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/38616">
    <dc:contributor>Mehlhorn, Hendrik</dc:contributor>
    <dc:language>eng</dc:language>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/38616/1/Mehlhorn_0-396389.pdf"/>
    <dc:rights>terms-of-use</dc:rights>
    <dc:creator>Lange, Matthias</dc:creator>
    <dc:creator>Schreiber, Falk</dc:creator>
    <dc:contributor>Scholz, Uwe</dc:contributor>
    <dcterms:abstract xml:lang="eng">Knowledge found in biomedical databases, in particular in Web information systems, is a major bioinformatics resource. In general, this biological knowledge is worldwide represented in a network of databases. These data is spread among thousands of databases, which overlap in content, but differ substantially with respect to content detail, interface, formats and data structure. To support a functional annotation of lab data, such as protein sequences, metabolites or DNA sequences as well as a semi-automated data exploration in information retrieval environments, an integrated view to databases is essential. Search engines have the potential of assisting in data retrieval from these structured sources, but fall short of providing a comprehensive knowledge except out of the interlinked databases. A prerequisite of supporting the concept of an integrated data view is to acquire insights into cross-references among database entities. This issue is being hampered by the fact, that only a fraction of all possible cross-references are explicitely tagged in the particular biomedical informations systems. In this work, we investigate to what extend an automated construction of an integrated data network is possible. We propose a method that predicts and extracts cross-references from multiple life science databases and possible referenced data targets. We study the retrieval quality of our method and report on first, promising results. The method is implemented as the tool IDPredictor, which is published under the DOI 10.5447/IPK/2012/4 and is freely available using the URL: http://dx.doi.org/10.5447/IPK/2012/4.</dcterms:abstract>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:contributor>Schreiber, Falk</dc:contributor>
    <dcterms:issued>2012-06-26</dcterms:issued>
    <dc:creator>Mehlhorn, Hendrik</dc:creator>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-04-26T09:13:55Z</dc:date>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/38616"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-04-26T09:13:55Z</dcterms:available>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/38616/1/Mehlhorn_0-396389.pdf"/>
    <dcterms:title>IDPredictor : predict database links in biomedical database</dcterms:title>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:contributor>Lange, Matthias</dc:contributor>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:creator>Scholz, Uwe</dc:creator>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
  </rdf:Description>
</rdf:RDF>
Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Kontakt
URL der Originalveröffentl.
Prüfdatum der URL
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Nein
Begutachtet
Diese Publikation teilen