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The Chemical Information Ontology: Provenance and Disambiguation for Chemical Data on the Biological Semantic Web

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Listed:
  • Janna Hastings
  • Leonid Chepelev
  • Egon Willighagen
  • Nico Adams
  • Christoph Steinbeck
  • Michel Dumontier

Abstract

Cheminformatics is the application of informatics techniques to solve chemical problems in silico. There are many areas in biology where cheminformatics plays an important role in computational research, including metabolism, proteomics, and systems biology. One critical aspect in the application of cheminformatics in these fields is the accurate exchange of data, which is increasingly accomplished through the use of ontologies. Ontologies are formal representations of objects and their properties using a logic-based ontology language. Many such ontologies are currently being developed to represent objects across all the domains of science. Ontologies enable the definition, classification, and support for querying objects in a particular domain, enabling intelligent computer applications to be built which support the work of scientists both within the domain of interest and across interrelated neighbouring domains. Modern chemical research relies on computational techniques to filter and organise data to maximise research productivity. The objects which are manipulated in these algorithms and procedures, as well as the algorithms and procedures themselves, enjoy a kind of virtual life within computers. We will call these information entities. Here, we describe our work in developing an ontology of chemical information entities, with a primary focus on data-driven research and the integration of calculated properties (descriptors) of chemical entities within a semantic web context. Our ontology distinguishes algorithmic, or procedural information from declarative, or factual information, and renders of particular importance the annotation of provenance to calculated data. The Chemical Information Ontology is being developed as an open collaborative project. More details, together with a downloadable OWL file, are available at http://code.google.com/p/semanticchemistry/ (license: CC-BY-SA).

Suggested Citation

  • Janna Hastings & Leonid Chepelev & Egon Willighagen & Nico Adams & Christoph Steinbeck & Michel Dumontier, 2011. "The Chemical Information Ontology: Provenance and Disambiguation for Chemical Data on the Biological Semantic Web," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-13, October.
  • Handle: RePEc:plo:pone00:0025513
    DOI: 10.1371/journal.pone.0025513
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    References listed on IDEAS

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    1. Christelle Reynès & Hélène Host & Anne-Claude Camproux & Guillaume Laconde & Florence Leroux & Anne Mazars & Benoit Deprez & Robin Fahraeus & Bruno O Villoutreix & Olivier Sperandio, 2010. "Designing Focused Chemical Libraries Enriched in Protein-Protein Interaction Inhibitors using Machine-Learning Methods," PLOS Computational Biology, Public Library of Science, vol. 6(3), pages 1-15, March.
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    Cited by:

    1. Antony J Williams & John Wilbanks & Sean Ekins, 2012. "Why Open Drug Discovery Needs Four Simple Rules for Licensing Data and Models," PLOS Computational Biology, Public Library of Science, vol. 8(9), pages 1-3, September.
    2. Marco Pritoni & Drew Paine & Gabriel Fierro & Cory Mosiman & Michael Poplawski & Avijit Saha & Joel Bender & Jessica Granderson, 2021. "Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis," Energies, MDPI, vol. 14(7), pages 1-37, April.

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