Citation: Baygi, S. F., Banerjee, S. K., Chakraborty, P., Kumar, Y., & Barupal, D. K. (2022). IDSL. UFA assigns high confidence molecular formula annotations for untargeted LC/HRMS datasets in metabolomics and exposomics. Analytical Chemistry 2022 https://pubs.acs.org/doi/full/10.1021/acs.analchem.2c00563 .

Contacts :

Sadjad Fakouri Baygi, PhD, Post-Doctoral Fellow, EMPH, Icahn School of Medicine at Mount Sinai, NY, USA (email: sadjad.fakouri-baygi@mssm.edu )

Dinesh Kumar Barupal, PhD, Assistant Professor, EMPH, Icahn School of Medicine at Mount Sinai, NY, USA (email : dinesh.kumar@mssm.edu)

GITHUB link:

For reporting of bugs, new features and other questions, please use the github issue reporting option https://github.com/idslme/IDSL.UFA/issues