CFM-ID: a web server for annotation, spectrum prediction and metabolite identification from tandem mass spectra

By Felicity Allen, Allison Pon, Michael Wilson, R. Greiner, David S. Wishart. Nucleic Acids Res., 2014

416 citations recorded by the source corpus.

CFM-ID is a web server supporting three tasks associated with the interpretation of tandem mass spectra (MS/MS) for the purpose of automated metabolite identification: annotation of the peaks in a spectrum for a known chemical structure; prediction of spectra for a given chemical structure and putative metabolite identification—a predicted ranking of possible candidate structures for a target spectrum. The algorithms used for these tasks are based on Competitive Fragmentation Modeling (CFM), a recently introduced probabilistic generative model for the MS/MS fragmentation process that uses machine learning techniques to learn its parameters from data. These algorithms have been extensively tested on multiple datasets and have been shown to out-perform existing methods such as MetFrag and FingerId. This web server provides a simple interface for using these algorithms and a graphical display of the resulting annotations, spectra and structures. CFM-ID is made freely available at http://cfmid.wishartlab.com.

Subfields: Computational Theory and Mathematics, Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/f658305a4887d9b1fee7056a34adf0db540cc31d

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Citations in the corpus

Searching molecular structure databases with tandem mass spectra using CSI:FingerID (2015, background): “For the general case, several strategies have been proposed during recent years, including simulation of mass spectra from molecular structure (10, 11), combinatorial fragmentation (12 – 17), and prediction of molecular fingerprints (18, 19).”
Software Tools and Approaches for Compound Identification of LC-MS/MS Data in Metabolomics (2018, background): “It is a very versatile approach useful for small molecules and peptides up to 1000 Da [72].”
Gut Microbiota-Derived Tryptophan Metabolites Modulate Inflammatory Response in Hepatocytes and Macrophages (2018, neutral): “Each feature was searched against spectral libraries in METLIN (Smith et al., 2005) and HMDB (Wishart et al., 2007) and analyzed using in silico fragmentation tools MetFrag (Wolf et al., 2010) and CFM-ID (Allen et al., 2014).”
HMDB 4.0: the human metabolome database for 2018 (2017, methodology): “In particular, CFM-ID (19) and CFMID 2.”
DrugBank 5.0: a major update to the DrugBank database for 2018 (2017, background): “In particular, CFM-ID (19) and CFM-ID 2.”
MolNetEnhancer: Enhanced Molecular Networks by Integrating Metabolome Mining and Annotation Tools (2019, background): “Metabolite annotation and identification tools have benefited from these advances as now more MS2 spectra per sample can be queried in reference libraries in order to find candidate structures or submitted to in silico tools that propose a putative structure [1–9].”