NORMAN Suspect List Exchange
Published May 10, 2023 | Version NORMAN-SLE-S75.0.2.0
Dataset Open

S75 | CyanoMetDB | Comprehensive database of secondary metabolites from cyanobacteria

Creators

  • 1. Eawag
  • 2. University of Birmingham
  • 3. University of São Paulo
  • 4. University of Gdansk
  • 5. University of Napoli Federico II
  • 6. National Research Council Canada
  • 7. University of Helsinki
  • 8. Martin Luther University Halle-Wittenberg
  • 9. University of Porto
  • 10. Technische Universität Dresden
  • 11. University of Bonn
  • 12. University of Potsdam
  • 13. University Marburg

Contributors

  • 1. LCSB, Uni Luxembourg

Description

This is the collection associated with list S75 CyanoMetDB Comprehensive database of secondary metabolites from cyanobacteria on the NORMAN Suspect List Exchange.

https://www.norman-network.com/nds/SLE/

CyanoMetDB is a comprehensive database of secondary metabolites from cyanobacteria manually curated from primary references described in Jones et al (2021), DOI: 10.1016/j.watres.2021.117017 (preprint DOI: 10.1101/2020.04.16.038703). This upload contains the 2023 release. Please cite Jones et al (2021) DOI: 10.1016/j.watres.2021.117017 and this record Janssen et al (2023) DOI: 10.5281/zenodo.7922070 when using this CyanoMetDB Version 2!

Contents:

CyanoMetDB XLSX database (2023 release): CyanoMetDB_v02_2023.xlsx

Additional files for workflows:

CSV format: CyanoMetDB_v02_2023.csv
MetFrag local CSV file (original database abridged and reformatted for use in MetFrag): CyanoMetDB_v02_2023_MetFrag.csv
Additional files for matching InChIKeys (rapid suspect flagging): CyanoMetDB_v02_2023_InChIKeys.txt

Notes

Please cite both the original work (Jones et al, 2020, DOI: 10.1016/j.watres.2021.117017) and this Zenodo deposition (Janssen et al, 2023, DOI: 10.5281/zenodo.7922070) when using CyanoMetDB Version 2.

Files

CyanoMetDB_v02_2023.csv

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Additional details

Related works

Is supplement to
Journal article: 10.1016/j.watres.2021.117017 (DOI)
https://www.norman-network.com/nds/SLE/ (URL)