Fig. 1: PrimeNovo stands as the pioneering biological non-autoregressive Transformer model, delivering precise peptide sequencing.

a Model architecture overview: Our model takes MS/MS spectra as input and generates the predicted peptide sequence. It comprises two key components: (1) a non-autoregressive Transformer model backbone optimized with connectionist temporal classification (CTC) loss, enabling simultaneous amino acid prediction at all positions. (2) The precise mass control (PMC) decoding unit, which utilizes predicted probabilities to precisely optimize peptide generation to meet mass requirements. b Applications and biological insights: PrimeNovo’s capabilities extend to downstream tasks and offer valuable insights for various biological investigations. c Average performance comparison: This chart illustrates the average performance of PrimeNovo alongside four other top-performing models on the widely utilized nine-species benchmark dataset (93,750 tested spectrum samples across all 9 species). Each bar represents the mean peptide recall for the respective approach. The black line indicates the 95% confidence interval (n = 9). Notably, results for DeepNovo, Casanovo, and Casanovo V2 are based on model weights released by the original authors, while PointNovo’s results are cited from the published work, as the original model weights were not shared by PointNovo’s authors. Source data are provided as a Source Data file. Some figures were created in BioRender⁵⁶.