Controlled vocabularies and semantics in systems biology

Mélanie Courtot(Terry Fox Research Institute), Nick Juty(European Bioinformatics Institute), Christian Knüpfer(Friedrich Schiller University Jena), Dagmar Waltemath(University of Rostock), Anna Zhukova(European Bioinformatics Institute), Andreas Dräger(University of Tübingen), Michel Dumontier(Carleton University), Andrew Finney(Ansys (United States)), Martin Golebiewski(Heidelberg Institute for Theoretical Studies), Janna Hastings(European Bioinformatics Institute), Stefan Hoops, Sarah Keating(European Bioinformatics Institute), Douglas B. Kell(University of Manchester), Samuel Kerrien(European Bioinformatics Institute), James R. Lawson(University of Auckland), Allyson Lister(Newcastle Hospitals - Campus for Ageing and Vitality), James Lu(École Polytechnique Fédérale de Lausanne), Rainer Machné(University of Vienna), Pedro Mendes(University of Manchester), Matthew Pocock(Newcastle University), Nicolás Rodríguez(European Bioinformatics Institute), Alice Villéger(University of Manchester), Darren J. Wilkinson(Newcastle Hospitals - Campus for Ageing and Vitality), Sarala Wimalaratne(European Bioinformatics Institute), Camille Laibe(European Bioinformatics Institute), Michael Hucka(California Institute of Technology), Nicolas Le Novère(European Bioinformatics Institute)
Molecular Systems Biology
October 25, 2011
Cited by 329Open Access
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Abstract

The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. Model structures, simulation descriptions and numerical results can be encoded in structured formats, but there is an increasing need to provide an additional semantic layer. Semantic information adds meaning to components of structured descriptions to help identify and interpret them unambiguously. Ontologies are one of the tools frequently used for this purpose. We describe here three ontologies created specifically to address the needs of the systems biology community. The Systems Biology Ontology (SBO) provides semantic information about the model components. The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of systems biology models, their characterization and interrelationships. The Terminology for the Description of Dynamics (TEDDY) categorizes dynamical features of the simulation results and general systems behavior. The provision of semantic information extends a model's longevity and facilitates its reuse. It provides useful insight into the biology of modeled processes, and may be used to make informed decisions on subsequent simulation experiments.


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