Annotating metabolite mass spectra with domain-inspired chemical formula transformers

S Goldman, J Wohlwend, M Stražar… - Nature Machine …, 2023 - nature.com
Metabolomics studies have identified small molecules that mediate cell signaling,
competition and disease pathology, in part due to large-scale community efforts to measure …

Prefix-tree decoding for predicting mass spectra from molecules

S Goldman, J Bradshaw, J Xin… - 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 …

MIST-CF: Chemical formula inference from tandem mass spectra

S Goldman, J Xin, 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 …

Spectrum of the past

MA Skinnider - Nature Reviews Chemistry, 2024 - nature.com
Thirty-four years ago, Curry and Rumelhart described a neural network-based approach to
annotate tandem mass spectra. Their ideas foreshadowed several important developments …

Contrastive learning-based embedder for the representation of tandem mass spectra

H Guo, K Xue, H Sun, W Jiang, S Pu - Analytical Chemistry, 2023 - ACS Publications
Tandem mass spectrometry (MS/MS) shows great promise in the research of metabolomics,
providing an abundance of information on compounds. Due to the rapid development of …

De novo peptide sequencing with InstaNovo: Accurate, database-free peptide identification for large scale proteomics experiments

K Eloff, K Kalogeropoulos, O Morell, A Mabona… - bioRxiv, 2023 - biorxiv.org
Bottom-up mass spectrometry-based proteomics is challenged by the task of identifying the
peptide that generates a tandem mass spectrum. Traditional methods that rely on known …

MS2Mol: A transformer model for illuminating dark chemical space from mass spectra

T Butler, A Frandsen, R Lightheart, B Bargh, J Taylor… - 2023 - chemrxiv.org
The ability to identify small molecules in complex samples from their mass spectra is among
the grand challenges of analytical chemistry. Improvements to this ability could significantly …

Mass2SMILES: deep learning based fast prediction of structures and functional groups directly from high-resolution MS/MS spectra.

D Elser, F Huber, E Gaquerel - bioRxiv, 2023 - biorxiv.org
Modern mass spectrometry-based metabolomics generates vast amounts of mass spectral
data as part of the chemical inventory of biospecimens. Annotation of the resulting MS/MS …

Machine Learning Methods for Discovering Metabolite Structures from Mass Spectra

SL Goldman - 2024 - dspace.mit.edu
Small molecule metabolites mediate myriad biological and environmental phenomena
across host-microbiome interactions, plant chemistry, cancer biology, and various other …

De novo peptide sequencing with InstaNovo: Diffusion-powered, peptide identification for large scale proteomics experiments

T Jenkins, K Eloff, K Kalogeropoulos, O Morell… - 2024 - researchsquare.com
Bottom-up mass spectrometry-based proteomics is challenged by the task of identifying the
peptide that generates a tandem mass spectrum. Traditional methods that rely on known …