Please cite:

Wang F, Allen D, Tian S, Oler E, Gautam V, Greiner R, Metz TO, and Wishart DS. (2022) CFM-ID 4.0–a web server for accurate MS-based metabolite identification. Nucleic Acids Research 50 (W1), W165-W174.

Wang F, Liigand J, Tian S, Arndt D, Greiner R, and Wishart D. (2021) CFM-ID 4.0: More Accurate ESI MS/MS Spectral Prediction and Compound Identification. Anal Chem. 93(34):11692-11700.

Djoumbou-Feunang Y, Pon A, Karu N, Zheng J, Li C, Arndt D, Gautam M, Allen F, and Wishart DS. (2019) Significantly Improved ESI-MS/MS Prediction and Compound Identification. Metabolites. 9(4):72.

Allen F, Greiner R, and Wishart DS (2016) Computational prediction of electron ionization mass spectra to assist in GC-MS compound identification. Anal Chem. 88(15):7689-97. Supporting Data

Allen F, Greiner R, and Wishart D (2015) Competitive fragmentation modeling of ESI-MS/MS spectra for putative metabolite identification. Metabolomics. 11:98–110. Supporting Data

Allen F, Pon A, Wilson M, Greiner R, and Wishart DS (2014). CFM-ID: a web server for annotation, spectrum prediction and metabolite identification from tandem mass spectra. Nucleic Acids Res. 42(Web Server issue):W94-9.

Source code:

• Machine-learned module (v4.0)
• Rule-based fragmentation tool

Docker:

• Docker image of command line version