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SUMMARY:Machine learning in chemistry and beyond" (ChE-651) seminar by Pro
 f. Emma Schymanski: "Environmental Cheminformatics - Searching for Meaning
  Amongst Millions of Chemicals"
DTSTART:20240917T151500
DTEND:20240917T161500
DTSTAMP:20260921T211552Z
UID:ed85c8a9a270f14dd5ac51f6ebaf5341e98e19ff5bff6ef3337c8480
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Emma Schymanski is chemist known for her work identifyin
 g unknown organic compounds\, particularly pollutants. She graduated with 
 a B.Sc. in Chemistry and a B.E. in Environmental Engineering from the Univ
 ersity of Western Australia in 2003. She completed her PhD at the Helmholt
 z Centre for Enironmental Research in Leipzig\, Germany in 2011\, and a po
 stdoc position at the Swiss Federal Institute of Aquatic Science and Techn
 ology. She is now head of the Environmental Cheminformatics Group as a Ful
 l Professor at the University of Luxembourg.\nExposomics researchers need 
 to identify relevant chemicals covering all potential exposures over entir
 e lifetimes. With over 100 million chemicals in the largest chemical datab
 ases\, coupled with broadly acknowledged knowledge gaps\, researchers are 
 faced with too much yet not enough information at the same time. Improveme
 nts in analytical technologies and computational mass spectrometry workflo
 ws coupled with the rapid growth in databases and increasing demand for hi
 gh throughput “big data” services from the research community present 
 significant challenges for both data hosts and workflow developers. This t
 alk will describe FAIR and Open Science developments in the Environmental 
 Cheminformatics group\, including the NORMAN Suspect List Exchange (NORMAN
 -SLE)\, MassBank\, MetFrag\, PubChemLite for Exposomics\, the PubChem PFAS
  Tree\, patRoon\, ShinyTPs and the Chemical Stripes\, and will show how th
 ese are applied in our active research projects to tackle challenges in no
 n-target exposomics studies. Finally\, this talk will touch on some of our
  latest work on patent data and critically assessing the implications of c
 lass definitions using the examples of per- and polyfluoroalkyl substances
  (PFAS) and persistent\, mobile\, toxic (PMT) compounds.
LOCATION:https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYI
 NRdz09
STATUS:CONFIRMED
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