{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Yang T"],"funding":["Research and Development Program of Guangzhou Laboratory","Chinese Ministry of Technology to Peng Cheng Laboratory","CAMS Innovation Fund for Medical Sciences","National Natural Science Foundation of China","National Key Research and Development Program of China"],"pagination":["bbae021"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10858680"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["25(2)"],"pubmed_abstract":["De novo peptide sequencing is a promising approach for novel peptide discovery, highlighting the performance improvements for the state-of-the-art models. The quality of mass spectra often varies due to unexpected missing of certain ions, presenting a significant challenge in de novo peptide sequencing. Here, we use a novel concept of complementary spectra to enhance ion information of the experimental spectrum and demonstrate it through conceptual and practical analyses. Afterward, we design suitable encoders to encode the experimental spectrum and the corresponding complementary spectrum and propose a de novo sequencing model $\\pi$-HelixNovo based on the Transformer architecture. We first demonstrated that $\\pi$-HelixNovo outperforms other state-of-the-art models using a series of compar"],"journal":["Briefings in bioinformatics"],"pubmed_title":["Introducing π-HelixNovo for practical large-scale de novo peptide sequencing."],"pmcid":["PMC10858680"],"funding_grant_id":["SRPG22-001","2019-I2M-5-063","2021YFA1301603","32088101","2020YFE0202200"],"pubmed_authors":["Ling T","He F","He Y","Sun B","Liang Z","Huang X","Xie L","Xu F","Chang C","Yang T","Wang Y","Li L"],"additional_accession":[]},"is_claimable":false,"name":"Introducing π-HelixNovo for practical large-scale de novo peptide sequencing.","description":"De novo peptide sequencing is a promising approach for novel peptide discovery, highlighting the performance improvements for the state-of-the-art models. The quality of mass spectra often varies due to unexpected missing of certain ions, presenting a significant challenge in de novo peptide sequencing. Here, we use a novel concept of complementary spectra to enhance ion information of the experimental spectrum and demonstrate it through conceptual and practical analyses. Afterward, we design suitable encoders to encode the experimental spectrum and the corresponding complementary spectrum and propose a de novo sequencing model $\\pi$-HelixNovo based on the Transformer architecture. We first demonstrated that $\\pi$-HelixNovo outperforms other state-of-the-art models using a series of compar","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Jan","modification":"2026-06-01T17:18:29.935Z","creation":"2025-04-03T23:50:01.787Z"},"accession":"S-EPMC10858680","cross_references":{"pubmed":["38340092"],"doi":["10.1093/bib/bbae021"]}}