InstaNovo glycopeptide fine-tuning

downstream-application · Transformer (AR)

InstaNovo glycopeptide fine-tuning: downstream-application · Transformer (AR). Adaptation of InstaNovo, a transformer de novo peptide sequencer, to glycoproteomics by fine-tuning on glycopeptide spectra. Learning from glyco spectra is measurable…

Adaptation of InstaNovo, a transformer de novo peptide sequencer, to glycoproteomics by fine-tuning on glycopeptide spectra. Learning from glyco spectra is measurable but limited, and every fine-tuning setting suffers catastrophic forgetting, losing accuracy on peptides the base model handled well; fine-tuning on unfiltered spectra that partly overlap the original training set gives the strongest learning signal but does not remove the effect. PCA of spectrum embeddings shows a large domain shift that explains the difficulty, and the study argues for treating overlapping glyco spectra as informative examples rather than outliers to discard, alongside multi-task and contrastive objectives and embedding transformations that pull glyco spectra toward the original distribution.

Kind downstream-application
Deep learning yes
Acquisition DDA
Family Transformer (AR)
Application area Glycoproteomics

Data

What the papers describing this method trained it on and reported its results on, as each paper states it. A version is named only where the paper names one.

Also used, purpose not recorded

Paper describing it

Authors (1)

Isaac H.J. Houngue

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