PhosSight: A Unified Deep Learning Framework Boosting and Accelerating Phosphoproteome Identification to Enable Biological Discoveries
Ben Wang, Zhiyuan Cheng, Chengying She, Hongwei Zhao, Jiahui Zhang, Lin Lv, Zhihao Yan, Hongwen Zhu, Lizhuang Liu, Yan Fu, Xinpei Yi · 2026
Read PhosSight: A Unified Deep Learning Framework Boosting and Accelerating Phosphoproteome Identification to Enable Biological Discoveries by Ben Wang, Zhiyuan Cheng, Chengying She, Hongwei Zhao, Jiahui Zhang, Lin Lv, Zhihao Yan, Hongwen Zhu, Lizhuang Liu, Yan Fu, Xinpei Yi (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13335961.txt.
Description
Ben Wang and colleagues present 2026 PhosSight, a unified deep learning framework boosting and accelerating phospho-protein finding to enable biological discoveries. Protein phospho-tagging is a key control of cell signals, with mass spectrometry based phospho-protein work serving as the top tech for its analysis. Phospho-tagging scans, however, are blocked by acquisition biases: DDA suffers from random gaps and missing values, while DIA faces computing logjams and waste from vast spectral lists.
PhosSight is a unified deep learning framework designed to boost finding depth and accelerate search speed. PhosSight features PhosDetect, a model that clearly encodes phospho traits to well predict peptide finding. For DDA, PhosSight uses predicted hold time, fragment strength, and finding to refine site finding and re-scoring, recovering borderline, low-level spectra. For DIA, PhosSight uses finding-guided list trimming to remove useless spectra.
Catalog record
| CREATOR | Ben Wang, Zhiyuan Cheng, Chengying She, Hongwei Zhao, Jiahui Zhang, Lin Lv, Zhihao Yan, Hongwen Zhu, Lizhuang Liu, Yan Fu, Xinpei Yi |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 89 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |