Scholarlink

Accurate identification of peptides from Data-Independent Acquisition (DIA) mass spectrometry data is crucial for discovering novel peptides and proteins. In this study, we introduce DiffNovo, which integrates transformer-based architectures with a diffusion model to enhance de novo peptide sequencing for DIA data. The experimental results demonstrate that DiffNovo outperforms existing state-of-the-art models in recall and precision for de novo peptide identification. DiffNovo achieves an average improvement of 20.7% in amino acid precision and an increase of 57.2% in peptide precision across various datasets. These substantial gains highlight the efficacy of DiffNovo in delivering accurate peptide sequencing from DIA mass spectrometry data.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

DiffNovo: A Transformer-Diffusion Model for De Novo Peptide Sequencing

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Shiva Ebrahimi,
  • Jiancheng Li,
  • Xuan Guo

摘要

Accurate identification of peptides from Data-Independent Acquisition (DIA) mass spectrometry data is crucial for discovering novel peptides and proteins. In this study, we introduce DiffNovo, which integrates transformer-based architectures with a diffusion model to enhance de novo peptide sequencing for DIA data. The experimental results demonstrate that DiffNovo outperforms existing state-of-the-art models in recall and precision for de novo peptide identification. DiffNovo achieves an average improvement of 20.7% in amino acid precision and an increase of 57.2% in peptide precision across various datasets. These substantial gains highlight the efficacy of DiffNovo in delivering accurate peptide sequencing from DIA mass spectrometry data.