Emma Schymanski

Professor Emma Schymanski is head of the Environmental Cheminformatics (ECI) group at the Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, FNR ATTRACT Fellow and special advisor to the rector for Open Science and Research Data Management. She served as Deputy Director of LCSB in 2024/5 (1 year mandate).

Biosketch

Professor Emma Schymanski has a double degree in Chemistry/ Environmental Engineering from UWA, Perth, completed her PhD at UFZ Leipzig and postdoc at Eawag, Switzerland. Her research combines cheminformatics and computational (high resolution) mass spectrometry approaches to elucidate the unknowns in complex samples, primarily with non-target screening, and relate these to environmental causes of disease. She is involved in many collaborative efforts, with >18,000 citations, >130 publications and a book.

An advocate for FAIR and open science, she is involved in several European and worldwide activities to improve the exchange of data, information and ideas between scientists, including the NORMAN Suspect List Exchange (NORMAN-SLE https://www.norman-network.com/nds/SLE/), MassBank (https://massbank.eu/MassBank/), MetFrag (https://msbi.ipb-halle.de/MetFrag/), PubChemLite for Exposomics (https://pubchemlite.lcsb.uni.lu/), the PubChem PFAS Tree (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=120), patRoon (https://rickhelmus.github.io/patRoon/), ShinyTPs (https://gitlab.com/uniluxembourg/lcsb/eci/shinytps) and the Chemical Stripes (https://gitlab.com/uniluxembourg/lcsb/eci/chemicalstripes).

Presentation

Exploring Relevant Chemical Space for Metabolomics and Exposomics with Open Science

Exposomics researchers need to identify relevant chemicals covering the entirety of potential exposures over entire lifetimes. With over 100 million chemicals in the largest chemical databases, coupled with broadly acknowledged knowledge gaps, researchers are faced with a seemingly impossible task. Although identification is still regarded as one of the bottlenecks of non-target mass spectrometry experiments, focus has shifted increasingly to interpretation, to maximise the benefits from this often still incomplete picture.

This keynote will cover several examples from the Environmental Cheminformatics group to show how open community developments can enhance the identification and interpretation of non-target high resolution mass spectrometry data in environmental, metabolomics and exposomics studies. This talk will show how enhancing the FAIRness (Findability, Accessibility, Interoperability and Reusability) of open resources can mutually enhance several resources for whole community benefit.

Open data exchange efforts help build knowledge, with activities such as MassBank (https://massbank.eu/MassBank/), the NORMAN Suspect List Exchange (NORMAN-SLE; https://normansle.lcsb.uni.lu/) and FAIR-TPs (https://fairtps.lcsb.uni.lu/), through to integrating this into workflows such as patRoon (https://rickhelmus.github.io/patRoon/).

These efforts in turn help define environmentally-relevant “chemical space” and the creation efficient yet informative subsets (e.g., PubChemLite for Exposomics; https://pubchemlite.lcsb.uni.lu/) for high throughput non-target screening. Methods such as patent mining, transformation prediction and other prioritization approaches help identify future chemicals of interest – and potential analytical gaps. Applications in the group will be used to showcase how these are applied in practice, from environmental monitoring through to identifying potential exposure modifiers related to disease progression in neurodegenerative disorders and rare disease cohorts.