Semantic systems biology: Formal knowledge representation in systems biology for model construction, retrieval, validation and discovery

Michel Dumontier*, Leonid L. Chepelev, Robert Hoehndorf

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Scopus citations


With the publication of the human genome, scientists worldwide opened champagne and let out a collective cheer for progress in biology. After all, the untold number of interactions of tens of thousands of genes, a greater number of their products and product derivatives, and tens of thousands of chemicals came much closer to complete characterization. Paradoxically however, while individual efforts produced important biological results, an integrated view of biology from systems perspective seemed ever more distant due to the complexity of data integration from multiple knowledge representation forms, formalisms, modeling paradigms, and conflicting scientific statements. To address this, semantic technologies have risen over the past decade with the promise of truly unifying biological knowledge and allowing cross-domain queries and model integration. In this chapter, we shall examine Semantic Web technologies and their applications to build, publish, query, discover, compare, validate, reason about, and evaluate models and knowledge in Systems Biology. We shall specifically address biological ontologies, open data repositories, modeling and annotation tools, and selected promising applications of Semantic Systems Biology. We firmly believe that it shall soon be possible to completely close the gap between facts, models, and results, and to fully apply the accrued models and facts to evaluate biological hypotheses on a system level, discovering meaning within the vast collection of biological knowledge and taking Systems Biology research to a new, unprecedented level.

Original languageEnglish (US)
Title of host publicationIntegrative Biology and Simulation Tools
PublisherSpringer Netherlands
Number of pages19
ISBN (Electronic)9789400768031
ISBN (Print)9400768028, 9789400768024
StatePublished - Aug 1 2013
Externally publishedYes

Bibliographical note

Publisher Copyright:
© Springer Science+Business Media Dordrecht 2013. All rights are reserved.


  • Artificial intelligence
  • Automated reasoning
  • Biochemistry
  • Bioinformatics
  • Biology
  • Computational biology
  • Description
  • Discovery
  • Formal knowledge representation
  • Identifier
  • Integration
  • Models
  • OWL
  • Ontology
  • Pathway
  • Protein
  • Query
  • RDF
  • Relation
  • SBML
  • Semantic annotation
  • Semantic web
  • Simulation
  • Small molecule
  • Sustainability
  • Systems biology
  • Type
  • Validation
  • World Wide Web

ASJC Scopus subject areas

  • General Medicine


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