Deep representation features from DreamDIAXMBD improve the analysis of data-independent acquisition proteomics
Gao et al. report DreamDIAXMBD, a deep learning-based tool, that can extract and score chromatogram features, improving the performance of peptide-centric DIA data analysis. In contrast to the existing tools, DreamDIAXMBD demonstrates higher numbers of precursor identifications and accurate quantifi...
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| Autors principals: | , , , , , , , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Nature Portfolio
2021-10-01
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| Col·lecció: | Communications Biology |
| Accés en línia: | https://doi.org/10.1038/s42003-021-02726-6 |
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