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      Interoperable genome annotation with GBOL, an extendable infrastructure for functional data mining

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      bioRxiv

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          Abstract

          Background: A standard structured format is used by the public sequence databases to present genome annotations. A prerequisite for a direct functional comparison is consistent annotation of the genetic elements with evidence statements. However, the current format provides limited support for data mining, hampering comparative analyses at large scale. Results: The provenance of a genome annotation describes the contextual details and derivation history of the process that resulted in the annotation. To enable interoperability of genome annotations, we have developed the Genome Biology Ontology Language (GBOL) and associated infrastructure (GBOL stack). GBOL is provenance aware and thus provides a consistent representation of functional genome annotations linked to the provenance. GBOL is modular in design, extendible and linked to existing ontologies. The GBOL stack of supporting tools enforces consistency within and between the GBOL definitions in the ontology (OWL) and the Shape Expressions (ShEx) language describing the graph structure. Modules have been developed to serialize the linked data (RDF) and to generate a plain text format files. Conclusion: The main rationale for applying formalized information models is to improve the exchange of information. GBOL uses and extends current ontologies to provide a formal representation of genomic entities, along with their properties and relations. The deliberate integration of data provenance in the ontology enables review of automatically obtained genome annotations at a large scale. The GBOL stack facilitates consistent usage of the ontology.

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          Author and article information

          Journal
          bioRxiv
          September 05 2017
          Article
          10.1101/184747
          b0548a9b-eb3e-4c9e-af13-31218a1535e2
          © 2017
          History

          Human biology,Genetics
          Human biology, Genetics

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