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Good practices and recommendations for using and benchmarking computational metabolomics metabolite annotation tools.

Niek F de JongeKevin MildauDavid MeijerJoris J R LouwenChristoph BüschlFlorian HuberJustin Johan Jozias van der Hooft
Published in: Metabolomics : Official journal of the Metabolomic Society (2022)
This review focuses on recent advances in mass spectral library-based and machine learning-supported metabolite annotation workflows. We discuss large-scale library matching and analogue search, the current bloom of mass spectral similarity scores, and how molecular networking has changed the field. In addition, the potentials and challenges of machine learning-supported metabolite annotation workflows are highlighted. Overall, recent developments in computational metabolomics have started to fundamentally change metabolomics workflows, and we expect that as a community we will be able to overcome current method performance ambiguities and annotation bottlenecks.
Keyphrases
  • machine learning
  • mass spectrometry
  • rna seq
  • healthcare
  • optical coherence tomography
  • artificial intelligence
  • primary care
  • big data
  • single cell
  • clinical practice
  • magnetic resonance imaging
  • single molecule