Casanovo

Casanovo predicts peptide sequences de novo from mass spectrometry proteomics data using a deep learning model.

Key Features:

• De novo peptide sequencing: Casanovo predicts peptide sequences directly from mass spectrometry data without requiring a reference database.
• Score interpretability enhancements: Improvements to the interpretability of scores assigned to predicted peptides were implemented.
• Database search generalization: The software was generalized for use in database search applications.
• Runtime optimization: Training and prediction runtimes were sped up.
• Workflows and visualization tools: Workflows and visualization tools facilitate adoption and interpretation of results.

Scientific Applications:

• Metaproteomics: Casanovo enables accurate peptide sequencing for metaproteomics applications.
• Antibody sequencing: Casanovo supports de novo sequencing of antibodies.
• Immunopeptidomics: Casanovo is applicable to immunopeptidomics studies.
• Novel peptide discovery: Casanovo enables discovery of novel peptide sequences in standard proteomics analyses.

Methodology:

Casanovo uses a deep learning model for de novo peptide sequencing from mass spectrometry proteomics data.