Wen-Feng Zeng
0000-0003-4325-2147
23 papers found
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The potential of plasma HLA peptides beyond neoepitopes
Robust dimethyl‐based multiplex‐DIA doubles single‐cell proteome depth via a reference channel
Quantitative multiorgan proteomics of fatal COVID‐19 uncovers tissue‐specific effects beyond inflammation
Enhancing Inter-link Coverage in Cross-Linking Mass Spectrometry through Context-Sensitive Subgrouping and Decoy Fusion
pGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level
Robust dimethyl-based multiplex-DIA workflow doubles single-cell proteome depth via a reference channel
AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics
AlphaViz: Visualization and validation of critical proteomics data directly at the raw data level
The structural context of PTMs at a proteome wide scale
Precise, fast and comprehensive analysis of intact glycopeptides and modified glycans with pGlyco3
AlphaPept, a modern and open framework for MS-based proteomics
pDeepXL: MS/MS Spectrum Prediction for Cross-Linked Peptide Pairs by Deep Learning
pDeep3: Toward More Accurate Spectrum Prediction with Fast Few-Shot Learning
Precise, Fast and Comprehensive Analysis of Intact Glycopeptides and Modified Saccharide Units with pGlyco3
Deep-Learning-Derived Evaluation Metrics Enable Effective Benchmarking of Computational Tools for Phosphopeptide Identification
Deep Learning in Proteomics
pDeep3: Towards More Accurate Spectrum Prediction with Fast Few-Shot Learning
MS/MS Spectrum Prediction for Modified Peptides Using pDeep2 Trained by Transfer Learning
pValid: Validation Beyond the Target-Decoy Approach for Peptide Identification in Shotgun Proteomics
pDeep: Predicting MS/MS Spectra of Peptides with Deep Learning
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