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H_References

Organised in alphabetical order:

  1. Allard, P.-M., Bisson, J. & Rutz, A. ISDB: In Silico Spectral Databases of Natural Products. Zenodo (2021).

  2. Allard, P.-M. et al. Integration of Molecular Networking and In-Silico MS/MS Fragmentation for Natural Products Dereplication. Anal Chem 88, 3317–3323 (2016).
  3. Barry A., T. Carboniferous Lepidodendraceae and Lepidocarpacea. ResearchGate (1978) doi:10.1007/BF02957853.
  4. Chambers, M. C. et al. A cross-platform toolkit for mass spectrometry and proteomics. Nat Biotechnol 30, 918–920 (2012).
  5. Consortium, T. D. B. G. I. The Digital Botanical Gardens Initiative. Manubot https://digital-botanical-gardens-initiative.github.io/dbgi-green-paper/ (2022).
  6. Consortium, T. E. The Earth Metabolome Initiative ... a brief presentation. (2022) doi:10.5281/zenodo.7486984.
  7. Djoumbou Feunang, Y. et al. ClassyFire: automated chemical classification with a comprehensive, computable taxonomy. J Cheminform 8, 61 (2016).
  8. Dührkop, K. et al. SIRIUS 4: a rapid tool for turning tandem mass spectra into metabolite structure information. Nat Methods 16, 299–302 (2019).
  9. Dührkop, K. et al. Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra. Nat Biotechnol 39, 462–471 (2021).
  10. Fairon-Demaret, M. Some uppermost Devonian megafloras: a stratigraphical review. asgb (1986).
  11. Guralnick, R. P. et al. Community Next Steps for Making Globally Unique Identifiers Work for Biocollections Data. Zookeys 133–154 (2015) doi:10.3897/zookeys.494.9352.
  12. Hallé, F. Aux origines des plantes. vol. Vol. 1 (Fayard, Paris, 2008).
  13. Lund, H. G. Definitions of Tree and Shrub. ResearchGate https://www.researchgate.net/publication/281743733_Definitions_of_'tree'_and_'shrub' (2015) doi:10.13140/RG.2.1.4103.9848.
  14. Meyer-Berthaud, B., Scheckler, S. E. & Wendt, J. Archaeopteris is the earliest known modern tree. Nature 398, 700–701 (1999).
  15. Myers, O. D., Sumner, S. J., Li, S., Barnes, S. & Du, X. One Step Forward for Reducing False Positive and False Negative Compound Identifications from Mass Spectrometry Metabolomics Data: New Algorithms for Constructing Extracted Ion Chromatograms and Detecting Chromatographic Peaks. Anal. Chem. 89, 8696–8703 (2017).
  16. Pluskal, T., Castillo, S., Villar-Briones, A. & Oresic, M. MZmine 2: modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data. BMC Bioinformatics 11, 395 (2010).
  17. Raven, J. & Crane, P. Trees. Current Biology 17, R303–R304 (2007).
  18. Rutz, A. et al. Taxonomically Informed Scoring Enhances Confidence in Natural Products Annotation. Front. Plant Sci. 10, (2019).
  19. Rutz, A. et al. The LOTUS initiative for open knowledge management in natural products research. Elife 11, e70780 (2022).
  20. Unifr. A propos | Jardin botanique de l’Université de Fribourg |. Unifr about JBUF https://www.unifr.ch/jardin-botanique/fr/about/.
  21. Wang, M. et al. Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking. Nat Biotechnol 34, 828–837 (2016).
  22. Kim, H. et al. NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products | Journal of Natural Products. https://pubs.acs.org/doi/10.1021/acs.jnatprod.1c00399.
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