Connecting metabolome and phenotype: recent advances in functional metabolomics tools for the identification of bioactive natural products

GA Vitale, C Geibel, V Minda, M Wang, AT Aron… - Natural Product …, 2024 - pubs.rsc.org
Covering: 1995 to 2023Advances in bioanalytical methods, particularly mass spectrometry,
have provided valuable molecular insights into the mechanisms of life. Non-targeted …

Computational methods for processing and interpreting mass spectrometry-based metabolomics

L Perez de Souza, AR Fernie - Essays in Biochemistry, 2024 - portlandpress.com
Metabolomics has emerged as an indispensable tool for exploring complex biological
questions, providing the ability to investigate a substantial portion of the metabolome …

Scientists' Perspectives on the Potential for Generative AI in their Fields

MR Morris - arxiv preprint arxiv:2304.01420, 2023 - arxiv.org
Generative AI models, including large language models and multimodal models that include
text and other media, are on the cusp of transforming many aspects of modern life, including …

Prefix-tree decoding for predicting mass spectra from molecules

S Goldman, J Bradshaw, J **n… - Advances in Neural …, 2023 - proceedings.neurips.cc
Computational predictions of mass spectra from molecules have enabled the discovery of
clinically relevant metabolites. However, such predictive tools are still limited as they occupy …

Tandem mass spectrum prediction for small molecules using graph transformers

A Young, H Röst, B Wang - Nature Machine Intelligence, 2024 - nature.com
Tandem mass spectra capture fragmentation patterns that provide key structural information
about molecules. Although mass spectrometry is applied in many areas, the vast majority of …

Generating molecular fragmentation graphs with autoregressive neural networks

S Goldman, J Li, CW Coley - Analytical Chemistry, 2024 - ACS Publications
The accurate prediction of tandem mass spectra from molecular structures has the potential
to unlock new metabolomic discoveries by augmenting the community's libraries of …

MIST-CF: Chemical formula inference from tandem mass spectra

S Goldman, J **n, J Provenzano… - Journal of Chemical …, 2023 - ACS Publications
Chemical formula annotation for tandem mass spectrometry (MS/MS) data is the first step
toward structurally elucidating unknown metabolites. While great strides have been made …

Differentiable modeling and optimization of non-aqueous Li-based battery electrolyte solutions using geometric deep learning

S Zhu, B Ramsundar, E Annevelink, H Lin… - Nature …, 2024 - nature.com
Electrolytes play a critical role in designing next-generation battery systems, by allowing
efficient ion transfer, preventing charge transfer, and stabilizing electrode-electrolyte …

Spiers Memorial Lecture: How to do impactful research in artificial intelligence for chemistry and materials science

AH Cheng, CT Ser, M Skreta, A Guzmán-Cordero… - Faraday …, 2025 - pubs.rsc.org
Machine learning has been pervasively touching many fields of science. Chemistry and
materials science are no exception. While machine learning has been making a great …

An Ensemble Spectral Prediction (ESP) model for metabolite annotation

X Li, Y Zhou Chen, A Kalia, H Zhu, L Liu… - …, 2024 - academic.oup.com
Motivation A key challenge in metabolomics is annotating measured spectra from a
biological sample with chemical identities. Currently, only a small fraction of measurements …