We are a group of Analytical Chemists who are passionate about application of Data Science and High Resolution Mass Spectrometry (HRMS) for unravelling the human and environmental exposome.
We build digital Machine Learning (ML) based tools to process LC/GC-HRMS data generated from complex samples from environmental to biological. These tools are to automize the data processing from the data import to structural elucidation and the assessment of quality of the identification. Additionally, we build models to maximize the level of information extracted from the spectra of structurally unknown chemicals. Our models take advantage the structural information implicitly present in the fragmentation pattern of an organic chemical. These complex models use a combination of chromatographic and mass spectrometric behavior of organic chemicals to infer about their environmental fate and toxicity.
All our tools are built following the FAIR Principals and made publicly available through GitHub and Bitbucket with MIT license.
New article - Assessment of the chemical space of NTA studies - September 20, 2023
New Publication - Spectral cleanup using CNLs - August 2, 2023
New Paper - A platform for community based NTA - April 1, 2023
New Publication - Predicting the toxicity category of chemicals - December 9, 2022
EMCMS presenting at International workshops on LC-MS/MS in environmental analysis and food safety (Barcelona) - October 10, 2022