DeepNovo Peptidome

downstream-application · CNN + RNN

DeepNovo Peptidome: downstream-application · CNN + RNN. Immunopeptidomics pipeline

Immunopeptidomics pipeline

Kind	downstream-application
Deep learning	yes
Acquisition	DDA
Family	CNN + RNN
Application area	Immunopeptidomics / neoantigen

Data

What the papers describing this method trained it on and reported its results on, as each paper states it. A version is named only where the paper names one.

Deposited

• A complete peptidome workflow for neoantigen identification and validation by mass spectrometry-based immunopeptidomics (as deposited) · 2023 preprint

Also used, purpose not recorded

• A complete peptidome workflow for neoantigen identification and validation by mass spectrometry-based immunopeptidomics (as deposited) · 2022 preprint
• The HLA-Ligand-Atlas. A resource of natural HLA ligands presented on benign tissues (as deposited) · 2022 preprint, 2023 preprint

Papers describing it (2)

• Discovering and Validating Neoantigens by Mass Spectrometry-based Immunopeptidomics and Deep Learning (2022, bioRxiv, preprint)
• A complete mass spectrometry-based immunopeptidomics pipeline for neoantigen identification and validation (2023, Research Square, preprint)

Paper using it

An application or evaluation that ran this method. It is not counted among its authors below.

• PeptidomicsDB: a unified resource of endogenous peptidomes for peptide discovery and functional exploration across species and biological contexts (2026, Nucleic Acids Research, peer-reviewed)

Authors (18)

Ngoc Hieu Tran, Chao Peng, Qingyang Lei, Lei Xin, Jingxiang Lang, Qing Zhang, Wenting Li, Haofei Miao, Ping Wu, Rui Qiao, Haiming Qin, Dongbo Bu, Haicang Zhang, Chungong Yu, Xiaolong Liu, Yi Zhang, Baozhen Shan, Ming Li

Seen in the charts

• The architectures
• Application areas
• Models and the authors behind them

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