Reference : Towards a harmonized identification scoring system in LC-HRMS/MS based non-target scr...
Scientific journals : Article
Life sciences : Environmental sciences & ecology
Computational Sciences
http://hdl.handle.net/10993/54240
Towards a harmonized identification scoring system in LC-HRMS/MS based non-target screening (NTS) of emerging contaminants
English
Alygizakis, Nikiforos [> >]
Lestremau, Francois [> >]
Gago-Ferrero, Pablo [> >]
Gil-Solsona, Rubén [> >]
Arturi, Katarzyna [> >]
Hollender, Juliane [> >]
Schymanski, Emma mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
Dulio, Valeria [> >]
Slobodnik, Jaroslav [> >]
Thomaidis, Nikolaos S. [> >]
2023
TrAC: Trends in Analytical Chemistry
159
116944
Yes
International
0165-9936
[en] Non-target screening (NTS) methods are rapidly gaining in popularity, empowering researchers to search for an ever-increasing number of chemicals. Given this possibility, communicating the confidence of identification in an automated, concise and unambiguous manner is becoming increasingly important. In this study, we compiled several pieces of evidence necessary for communicating NTS identification confidence and developed a machine learning approach for classification of the identifications as reliable and unreliable. The machine learning approach was trained using data generated by four laboratories equipped with different instrumentation. The model discarded substances with insufficient identification evidence efficiently, while revealing the relevance of different parameters for identification. Based on these results, a harmonized IP-based system is proposed. This new NTS-oriented system is compatible with the currently widely used five level system. It increases the precision in reporting and the reproducibility of current approaches via the inclusion of evidence scores, while being suitable for automation.
Researchers ; Professionals ; Students ; General public
http://hdl.handle.net/10993/54240
10.1016/j.trac.2023.116944
https://linkinghub.elsevier.com/retrieve/pii/S0165993623000316
All rights reserved
FnR ; FNR12341006 > Emma Schymanski > ECHIDNA > Environmental Cheminformatics To Identify Unknown Chemicals And Their Effects > 01/10/2018 > 30/09/2023 > 2018

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