Automated fragment formula annotation for electron ionisation, high resolution mass spectrometry: application to atmospheric measurements of halocarbons.
Myriam GuillevicAurore GuillevicMartin K VollmerPaul SchlauriMatthias HillLukas EmmeneggerStefan ReimannPublished in: Journal of cheminformatics (2021)
Our method enables to reconstruct most probable chemical formulae independently from spectral databases. Therefore, it demonstrates the suitability of EI-HRMS data for non-target analysis and paves the way for the identification of substances for which no EI mass spectrum is registered in databases. We illustrate the performances of our method for atmospheric trace gases and suggest that it may be well suited for many other types of samples. The L-GPL licenced Python code is released under the name ALPINAC for ALgorithmic Process for Identification of Non-targeted Atmospheric Compounds.
Keyphrases
- high resolution mass spectrometry
- particulate matter
- liquid chromatography
- big data
- ultra high performance liquid chromatography
- gas chromatography
- bioinformatics analysis
- machine learning
- carbon dioxide
- air pollution
- tandem mass spectrometry
- high throughput
- cancer therapy
- heavy metals
- electronic health record
- human milk
- risk assessment
- magnetic resonance
- drug delivery
- computed tomography
- high resolution
- electron transfer