Aber-OWL: a framework for ontology-based data access in biology
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  • 作者:Robert Hoehndorf (1) (2)
    Luke Slater (1) (2) (3)
    Paul N Schofield (4)
    Georgios V Gkoutos (3)

    1. Computational Bioscience Research Center
    ; King Abdullah University of Science and Technology ; 4700 KAUST ; Thuwal ; 23955-6900 ; Saudi Arabia
    2. Computer
    ; Electrical and Mathematical Sciences & Engineering Division ; King Abdullah University of Science and Technology ; 4700 KAUST ; Thuwal ; 23955-6900 ; Saudi Arabia
    3. Department of Computer Science
    ; Aberystwyth University ; Llandinam Building ; Aberystwyth ; SY23 3DB ; UK
    4. Department of Physiology
    ; Development & Neuroscience ; University of Cambridge ; Downing Street ; Cambridge ; CB2 3EG ; UK
  • 关键词:Ontology ; based data access ; Linked data ; OWL
  • 刊名:BMC Bioinformatics
  • 出版年:2015
  • 出版时间:December 2015
  • 年:2015
  • 卷:16
  • 期:1
  • 全文大小:799 KB
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  • 刊物主题:Bioinformatics; Microarrays; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Combinatorial Libraries; Algorithms;
  • 出版者:BioMed Central
  • ISSN:1471-2105
文摘
Background Many ontologies have been developed in biology and these ontologies increasingly contain large volumes of formalized knowledge commonly expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within these ontologies relies on the use of automated reasoning. Results We have developed the Aber-OWL infrastructure that provides reasoning services for bio-ontologies. Aber-OWL consists of an ontology repository, a set of web services and web interfaces that enable ontology-based semantic access to biological data and literature. Aber-OWL is freely available at http://aber-owl.net. Conclusions Aber-OWL provides a framework for automatically accessing information that is annotated with ontologies or contains terms used to label classes in ontologies. When using Aber-OWL, access to ontologies and data annotated with them is not merely based on class names or identifiers but rather on the knowledge the ontologies contain and the inferences that can be drawn from it.

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