Machine learning-assisted identification of environmental pollutants by liquid chromatography coupled with high-resolution mass spectrometry
Chemical exposure can be linked with various adverse effects, but the causal association is
still poorly understood. To meet the challenge, non-target screening (NTS) based on liquid …
still poorly understood. To meet the challenge, non-target screening (NTS) based on liquid …
Prediction of liquid chromatographic retention time with graph neural networks to assist in small molecule identification
The predicted liquid chromatographic retention times (RTs) of small molecules are not
accurate enough for wide adoption in structural identification. In this study, we used the …
accurate enough for wide adoption in structural identification. In this study, we used the …
Automated method development in high-pressure liquid chromatography
E Bosten, A Kensert, G Desmet, D Cabooter - Journal of Chromatography A, 2024 - Elsevier
Method development in liquid chromatography is a crucial step in the optimization of
analytical separations for various applications. However, it is often a challenging endeavour …
analytical separations for various applications. However, it is often a challenging endeavour …
Deep learning for retention time prediction in reversed-phase liquid chromatography
ES Fedorova, DD Matyushin, IV Plyushchenko… - … of Chromatography A, 2022 - Elsevier
Retention time prediction in high-performance liquid chromatography (HPLC) is the subject
of many studies since it can improve the identification of unknown molecules in untargeted …
of many studies since it can improve the identification of unknown molecules in untargeted …
Joint structural annotation of small molecules using liquid chromatography retention order and tandem mass spectrometry data
Structural annotation of small molecules in biological samples remains a key bottleneck in
untargeted metabolomics, despite rapid progress in predictive methods and tools during the …
untargeted metabolomics, despite rapid progress in predictive methods and tools during the …
[HTML][HTML] Development of a single retention time prediction model integrating multiple liquid chromatography systems: application to new psychoactive substances
Database-driven suspect screening has proven to be a useful tool to detect new
psychoactive substances (NPS) outside the scope of targeted screening; however, the lack …
psychoactive substances (NPS) outside the scope of targeted screening; however, the lack …
Retention time prediction with message-passing neural networks
Retention time prediction, facilitated by advances in machine learning, has become a useful
tool in untargeted LC-MS applications. State-of-the-art approaches include graph neural …
tool in untargeted LC-MS applications. State-of-the-art approaches include graph neural …
Retention time dataset for heterogeneous molecules in reversed–phase liquid chromatography
Y Zhang, F Liu, XQ Li, Y Gao, KC Li, QH Zhang - Scientific Data, 2024 - nature.com
Quantitative structure–property relationships have been extensively studied in the field of
predicting retention times in liquid chromatography (LC). However, making transferable …
predicting retention times in liquid chromatography (LC). However, making transferable …
Probabilistic metabolite annotation using retention time prediction and meta-learned projections
Retention time information is used for metabolite annotation in metabolomic experiments.
But its usefulness is hindered by the availability of experimental retention time data in …
But its usefulness is hindered by the availability of experimental retention time data in …
Gas chromatographic retention index prediction using multimodal machine learning
DD Matyushin, AK Buryak - Ieee Access, 2020 - ieeexplore.ieee.org
Gas chromatography is a widely used method in analytical chemistry and metabolomics.
Using gas chromatography, vaporizable compounds can be separated for their further …
Using gas chromatography, vaporizable compounds can be separated for their further …