Yet another great collaboration with @oyanes.bsky.social

As a proof of concept, we successfully annotate three previously unidentified compounds frequently found in human samples

Our results demonstrate that SingleFrag surpasses state-of-the-art in silico fragmentation tools, providing a powerful method for annotating unknown MS/MS spectra of known compounds

Here, we present #SingleFrag, a novel deep learning tool that predicts individual MS/MS fragments separately, rather than attempting to predict the entire fragmentation spectrum at once

Identifying metabolites in MS/MS data often means matching experimental spectra with existing spectral libraries. But, with limited libraries, identifying unknowns remains a big hurdle in #metabolomics

Thanks 🙏🙏 @martikagv.bsky.social @vcolizza.bsky.social @pessoabrain.bsky.social @asteixeira.bsky.social @gomezgardenes.bsky.social @seeslab.bsky.social (and all the speakers not in this platform) for their amazing contribution to make this edition a reference for young Network Scientists.

Great work by first author Manuel Ruiz-Botella!

Leveraging the model’s efficiency, we created a database of 8.2M synthetically generated molecules and conducted a Turing-like test with organic chemistry experts to further assess the plausibility of the generated molecules, and potential biases and limitations of #CoCoGraph

#CoCoGraph outperforms state-of-the-art approaches on standard benchmarks while requiring up to an order of magnitude fewer parameters