Baylor College of Medicine
Houston, USA · 7 authors
Baylor College of Medicine (Houston, USA): 7 authors and 12 papers in the de novo peptide sequencing catalog.
Departments
- Department of Molecular and Human Genetics
- Lester and Sue Smith Breast Center
Papers (12)
- AI proteomics: from protein identification to virtual cells (2026, Nature Methods)
- CasanovoGUI: a cross-platform desktop application for deep learning-based de novo peptide sequencing with Casanovo (2026, bioRxiv)
- Improvements to Casanovo, a Deep Learning De Novo Peptide Sequencer (2025, Journal of Proteome Research)
- Improvements to CasaNovo, a deep learning de novo peptide sequencer (2025, bioRxiv)
- A transformer model for de novo sequencing of data independent acquisition mass spectrometry data (2025, Nature Methods)
- Deep Learning Methods for De Novo Peptide Sequencing (2024, Mass Spectrometry Reviews)
- A multi-species benchmark for training and validating mass spectrometry proteomics machine learning models (2024, Scientific Data)
- A multi-species benchmark for training and validating mass spectrometry proteomics machine learning models (2024, ChemRxiv)
- A transformer model for de novo sequencing of data independent acquisition mass spectrometry data (2024, bioRxiv)
- Deep Learning in Proteomics (2020, Proteomics)
- Ultrahigh‐resolution Fourier transform ion cyclotron resonance mass spectrometry and tandem mass spectrometry for peptide de novo amino acid sequencing for a seven‐protein mixture by paired single‐residue transposed Lys‐N and Lys‐C digestion (2017, Rapid Communications in Mass Spectrometry)
- Paired single residue‐transposed Lys‐N and Lys‐C digestions for label‐free identification of N‐terminal and C‐terminal MS/MS peptide product ions: ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry and tandem mass spectrometry for peptide de novo sequencing (2015, Rapid Communications in Mass Spectrometry)