Controlled vocabularies and semantics in systems biology

Mélanie Courtot; Nick Juty; Christian Knüpfer; Dagmar Waltemath; Anna Zhukova; Andreas Dräger; Michel Dumontier; Andrew Finney; Martin Golebiewski; Janna Hastings; Stefan Hoops; Sarah Keating; Douglas B. Kell; Samuel Kerrien; James Lawson; Allyson Lister; James Lu; Rainer MacHne; Pedro Mendes; Matthew Pocock; Nicolas Rodriguez; Alice Villeger; Darren J. Wilkinson; Sarala Wimalaratne; Camille Laibe; Michael Hucka; Nicolas Le Novère

doi:10.1038/msb.2011.77

Controlled vocabularies and semantics in systems biology

Mélanie Courtot, Nick Juty, Christian Knüpfer, Dagmar Waltemath, Anna Zhukova, Andreas Dräger, Michel Dumontier, Andrew Finney, Martin Golebiewski, Janna Hastings, Stefan Hoops, Sarah Keating, Douglas B. Kell, Samuel Kerrien, James Lawson, Allyson Lister, James Lu, Rainer MacHne, Pedro Mendes, Matthew PocockNicolas Rodriguez, Alice Villeger, Darren J. Wilkinson, Sarala Wimalaratne, Camille Laibe, Michael Hucka, Nicolas Le Novère

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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. © 2011 EMBO and Macmillan Publishers Limited.

Original language	English
Article number	543
Journal	Molecular Systems Biology
Volume	7
DOIs	https://doi.org/10.1038/msb.2011.77
Publication status	Published - 2011

Keywords

dynamics
kinetics
model
ontology
simulation

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Courtot, M., Juty, N., Knüpfer, C., Waltemath, D., Zhukova, A., Dräger, A., Dumontier, M., Finney, A., Golebiewski, M., Hastings, J., Hoops, S., Keating, S., Kell, D. B., Kerrien, S., Lawson, J., Lister, A., Lu, J., MacHne, R., Mendes, P., ... Le Novère, N. (2011). Controlled vocabularies and semantics in systems biology. Molecular Systems Biology, 7, Article 543. https://doi.org/10.1038/msb.2011.77

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title = "Controlled vocabularies and semantics in systems biology",

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. {\textcopyright} 2011 EMBO and Macmillan Publishers Limited.",

keywords = "dynamics, kinetics, model, ontology, simulation",

author = "M{\'e}lanie Courtot and Nick Juty and Christian Kn{\"u}pfer and Dagmar Waltemath and Anna Zhukova and Andreas Dr{\"a}ger and Michel Dumontier and Andrew Finney and Martin Golebiewski and Janna Hastings and Stefan Hoops and Sarah Keating and Kell, {Douglas B.} and Samuel Kerrien and James Lawson and Allyson Lister and James Lu and Rainer MacHne and Pedro Mendes and Matthew Pocock and Nicolas Rodriguez and Alice Villeger and Wilkinson, {Darren J.} and Sarala Wimalaratne and Camille Laibe and Michael Hucka and {Le Nov{\`e}re}, Nicolas",

note = "We thank the National Institute of General Medical Sciences, European Commission (FP7 SP4 Capacities Preparatory Phase 211601, ELIXIR) and Marie-Curie BioStar for providing resources to carry out this work.",

year = "2011",

doi = "10.1038/msb.2011.77",

language = "English",

volume = "7",

journal = "Molecular Systems Biology",

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Courtot, M, Juty, N, Knüpfer, C, Waltemath, D, Zhukova, A, Dräger, A, Dumontier, M, Finney, A, Golebiewski, M, Hastings, J, Hoops, S, Keating, S, Kell, DB, Kerrien, S, Lawson, J, Lister, A, Lu, J, MacHne, R, Mendes, P, Pocock, M, Rodriguez, N, Villeger, A, Wilkinson, DJ, Wimalaratne, S, Laibe, C, Hucka, M & Le Novère, N 2011, 'Controlled vocabularies and semantics in systems biology', Molecular Systems Biology, vol. 7, 543. https://doi.org/10.1038/msb.2011.77

TY - JOUR

T1 - Controlled vocabularies and semantics in systems biology

AU - Courtot, Mélanie

AU - Juty, Nick

AU - Knüpfer, Christian

AU - Waltemath, Dagmar

AU - Zhukova, Anna

AU - Dräger, Andreas

AU - Dumontier, Michel

AU - Finney, Andrew

AU - Golebiewski, Martin

AU - Hastings, Janna

AU - Hoops, Stefan

AU - Keating, Sarah

AU - Kell, Douglas B.

AU - Kerrien, Samuel

AU - Lawson, James

AU - Lister, Allyson

AU - Lu, James

AU - MacHne, Rainer

AU - Mendes, Pedro

AU - Pocock, Matthew

AU - Rodriguez, Nicolas

AU - Villeger, Alice

AU - Wilkinson, Darren J.

AU - Wimalaratne, Sarala

AU - Laibe, Camille

AU - Hucka, Michael

AU - Le Novère, Nicolas

N1 - We thank the National Institute of General Medical Sciences, European Commission (FP7 SP4 Capacities Preparatory Phase 211601, ELIXIR) and Marie-Curie BioStar for providing resources to carry out this work.

PY - 2011

Y1 - 2011

N2 - 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. © 2011 EMBO and Macmillan Publishers Limited.

AB - 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. © 2011 EMBO and Macmillan Publishers Limited.

KW - dynamics

KW - kinetics

KW - model

KW - ontology

KW - simulation

U2 - 10.1038/msb.2011.77

DO - 10.1038/msb.2011.77

M3 - Article

C2 - 22027554

SN - 1744-4292

VL - 7

JO - Molecular Systems Biology

JF - Molecular Systems Biology

M1 - 543

ER -

Controlled vocabularies and semantics in systems biology

Abstract

Keywords

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