{"ID":2829528,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.12272","arxiv_id":"2512.12272","title":"Accurate de novo sequencing of the modified proteome with OmniNovo","abstract":"Post-translational modifications (PTMs) serve as a dynamic chemical language regulating protein function, yet current proteomic methods remain blind to a vast portion of the modified proteome. Standard database search algorithms suffer from a combinatorial explosion of search spaces, limiting the identification of uncharacterized or complex modifications. Here we introduce OmniNovo, a unified deep learning framework for reference-free sequencing of unmodified and modified peptides directly from tandem mass spectra. Unlike existing tools restricted to specific modification types, OmniNovo learns universal fragmentation rules to decipher diverse PTMs within a single coherent model. By integrating a mass-constrained decoding algorithm with rigorous false discovery rate estimation, OmniNovo achieves state-of-the-art accuracy, identifying 51\\% more peptides than standard approaches at a 1\\% false discovery rate. Crucially, the model generalizes to biological sites unseen during training, illuminating the dark matter of the proteome and enabling unbiased comprehensive analysis of cellular regulation.","short_abstract":"Post-translational modifications (PTMs) serve as a dynamic chemical language regulating protein function, yet current proteomic methods remain blind to a vast portion of the modified proteome. Standard database search algorithms suffer from a combinatorial explosion of search spaces, limiting the identification of unch...","url_abs":"https://arxiv.org/abs/2512.12272","url_pdf":"https://arxiv.org/pdf/2512.12272v1","authors":"[\"Yuhan Chen\",\"Shang Qu\",\"Zhiqiang Gao\",\"Yuejin Yang\",\"Xiang Zhang\",\"Sheng Xu\",\"Xinjie Mao\",\"Liujia Qian\",\"Jiaqi Wei\",\"Zijie Qiu\",\"Chenyu You\",\"Lei Bai\",\"Ning Ding\",\"Tiannan Guo\",\"Bowen Zhou\",\"Siqi Sun\"]","published":"2025-12-13T10:27:14Z","proceeding":"q-bio.QM","tasks":"[\"q-bio.QM\",\"cs.AI\"]","methods":"[]","has_code":false}