SABIO-Reaction Kinetics Database

SABIO-RK (System for the Analysis of Biochemical Pathways - Reaction Kinetics) is a web-accessible database storing information about biochemical reactions and their kinetic properties.

SABIO-RK Database
Content
DescriptionDatabase for biochemical reactions and their kinetic properties
Data types
captured
Quantitative information on reaction dynamics
Organismsall
Contact
Research centerHeidelberger Institut für Theoretische Studien
LaboratoryScientific Databases and Visualization
Release date2006
Access
Websitehttp://sabio.h-its.org
Web service URLhttp://sabio.h-its.org/layouts/content/webservices.gsp
Miscellaneous
Licensehttp://sabio.h-its.org/layouts/content/termscondition.gsp
Curation policyCurated database

SABIO-RK comprises a reaction-oriented representation of quantitative information on reaction dynamics based on a given selected publication. This comprises all available kinetic parameters together with their corresponding rate equations, as well as kinetic law and parameter types and experimental and environmental conditions under which the kinetic data were determined. Additionally, SABIO-RK contains information about the underlying biochemical reactions and pathways including their reaction participants, cellular location and detailed information about the enzymes catalysing the reactions.[1][2][3][4][5]

SABIO-RK Database Content

The data stored in SABIO-RK in a comprehensive manner is mainly extracted manually from literature. This includes reactions, their participants (substrates, products), modifiers (inhibitors, activators, cofactors), catalyst details (e.g. EC enzyme classification, protein complex composition, wild type / mutant information), kinetic parameters together with corresponding rate equation, biological sources (organism, tissue, cellular location), environmental conditions (pH, temperature, buffer) and reference details. Data are adapted, normalized and annotated to controlled vocabularies, ontologies and external data sources including KEGG, UniProt, ChEBI, PubChem, NCBI, Reactome, BRENDA, MetaCyc, BioModels, and PubMed.
As of September 2019 SABIO-RK contains more than 60.000 curated single entries extracted from more than 6.000 publications.
Several tools, databases and workflows in Systems Biology make use of SABIO-RK biochemical reaction data by integration into their framework including SYCAMORE,[6] MeMo-RK,[7] CellDesigner,[8] PeroxisomeDB,[9] Taverna workflows or tools like KineticsWizard software for data capture and analysis.[10] Additionally, SABIO-RK is part of MIRIAM registry, a set of guidelines for the annotation and curation of computational models[11][12]

SABIO-RK Database Access

The usage of SABIO-RK is free of charge. Commercial users need a license. SABIO-RK offers several ways for data access:

  • a browser-based interface
  • RESTful-based web services for programmatic access

Result data sets can be exported in different formats including SBML, BioPAX/SBPAX, and table format.

References

  1. Wittig, U; Rey, M; Weidemann, A; Kania, R; Müller, W (4 January 2018). "SABIO-RK: an updated resource for manually curated biochemical reaction kinetics". Nucleic Acids Research. 46 (D1): D656–D660. doi:10.1093/nar/gkx1065. PMC 5753344. PMID 29092055.
  2. Wittig, U; Kania, R; Golebiewski, M; Rey, M; Shi, L; Jong, L; Algaa, E; Weidemann, A; Sauer-Danzwith, H; Mir, S; Krebs, O; Bittkowski, M; Wetsch, E; Rojas, I; Müller, W (January 2012). "SABIO-RK--database for biochemical reaction kinetics". Nucleic Acids Research. 40 (Database issue): D790-6. doi:10.1093/nar/gkr1046. PMC 3245076. PMID 22102587.
  3. Rojas, I; Golebiewski, M; Kania, R; Krebs, O; Mir, S; Weidemann, A; Wittig, U (2007). "Storing and annotating of kinetic data". In Silico Biology. 7 (2 Suppl): S37–44. PMID 17822389.
  4. Wittig, Ulrike; Golebiewski, Martin; Kania, Renate; Krebs, Olga; Mir, Saqib; Weidemann, Andreas; Anstein, Stefanie; Saric, Jasmin; Rojas, Isabel (2006). "SABIO-RK: Integration and Curation of Reaction Kinetics Data". Data Integration in the Life Sciences. Lecture Notes in Computer Science. 4075. pp. 94–103. doi:10.1007/11799511_9. ISBN 978-3-540-36593-8.
  5. Müller W. In: Pfade im Informationsdschungel Spektrum der Wissenschaft, Spektrum Spezial: Datengetriebene Wissenschaft, December 2011
  6. Weidemann, A.; Richter, S.; Stein, M.; Sahle, S.; Gauges, R.; Gabdoulline, R.; Surovtsova, I.; Semmelrock, N.; et al. (2008). "SYCAMORE--a systems biology computational analysis and modeling research environment". Bioinformatics. 24 (12): 1463–4. doi:10.1093/bioinformatics/btn207. PMID 18463116.
  7. Swainston, Neil; Golebiewski, Martin; Messiha, Hanan L.; Malys, Naglis; Kania, Renate; Kengne, Sylvestre; Krebs, Olga; Mir, Saqib; et al. (2010). "Enzyme kinetics informatics: From instrument to browser". FEBS Journal. 277 (18): 3769–79. CiteSeerX 10.1.1.659.3420. doi:10.1111/j.1742-4658.2010.07778.x. PMID 20738395.
  8. Funahashi, A; Jouraku, A; Matsuoka, Y; Kitano, H (2007). "Integration of CellDesigner and SABIO-RK". In Silico Biology. 7 (2 Suppl): S81–90. PMID 17822394.
  9. Schluter, A.; Real-Chicharro, A.; Gabaldon, T.; Sanchez-Jimenez, F.; Pujol, A. (2009). "PeroxisomeDB 2.0: An integrative view of the global peroxisomal metabolome". Nucleic Acids Research. 38 (Database issue): D800–5. doi:10.1093/nar/gkp935. PMC 2808949. PMID 19892824.
  10. Messiha, Hanan L.; Malys, Naglis; Carroll, Kathleen M. (2011). "Towards a Full Quantitative Description of Yeast Metabolism". Methods in Systems Biology. Methods in Enzymology. 500. pp. 215–231. doi:10.1016/B978-0-12-385118-5.00012-8. ISBN 978-0-12-385118-5. PMID 21943900.
  11. Juty, N.; Le Novere, N.; Laibe, C. (2011). "Identifiers.org and MIRIAM Registry: Community resources to provide persistent identification". Nucleic Acids Research. 40 (Database issue): D580–6. doi:10.1093/nar/gkr1097. PMC 3245029. PMID 22140103.
  12. SABIO-RK as part of MIRIAM Registry

External References


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