RT @sees_lab: New paper out in @OxfordJournals Briefings in Bioinformatics. 📰SingleFrag: a deep learning tool for MS/MS fragment and spectr….

Yet another great collaboration with @yaneslab.

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.

New paper out in @OxfordJournals Briefings in Bioinformatics. 📰SingleFrag: a deep learning tool for MS/MS fragment and spectral prediction and metabolite annotation

RT @sees_lab: New preprint out in the @arxiv!. We introduce #CoCoGraph, a collaborative and constrained graph diffusion model capable of ge….

Great work by first author @manu_ru_bo!.

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

New preprint out in the @arxiv!. We introduce #CoCoGraph, a collaborative and constrained graph diffusion model capable of generating molecules that are guaranteed to be chemically valid

RT @BagariaJoan: @icreacommunity.

RT @universitatURV: 🧠Comparar cervells per entendre com es connecten les neurones i com aquestes connexions poden variar entre espècies o i….

RT @sees_lab: 💡Our paper on probabilistic alignment of networks has been highlighted by Nature Communications as one the 50 best papers rec….

💡Our paper on probabilistic alignment of networks has been highlighted by Nature Communications as one the 50 best papers recently published in the area of Applied physics and mathematics 📰Read the paper

At #NetSci2025 today? Don't miss Gemma Bel's talk at the #SINM satellite. 📰 Model-based alignment of developing connectomes.📍 Conference hall EPD150.🕓 14:30

At #NetSci2025 today? Don't miss Manuel Ruiz-Botella's talk at the #SINM satellite. 📰 CoCoGraph: A collaborative constrained graph diffusion model for the generation of graphs with fixed degree sequences.📍 Conference hall EPD150. 🕓 16:30. 🔗to paper:

RT @netbiomed2025: We just had an amazing talk by Manuel Ruiz-Botella, who introduced us to #CoCoGraph, a graph diffusion model for the gen….

RT @sees_lab: At #NetSci2025? Don't miss Teresa Lazaros's talk today at the Neuroscience satellite. 📰 Probabilistic network alignment appli….