Author

Qingyang Lei

Zhengzhou University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:proteomics· 2 Research Focus:benchmarking· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

Chao PengiD· 2 shared Chungong YuiD· 2 shared Dongbo BuiD· 2 shared Haiming QiniD· 2 shared Jingxiang Lang· 2 shared Ngoc Hieu TraniD· 2 shared Baozhen ShaniD· 1 shared Haicang ZhangiD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Chao PengORCID

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Author profile →

2 papers

Recent·Most cited

Predicting TCR-pMHC Binding by Reinforcement Learning

Jingxiang Lang, Chungong Yu, Ngoc Hieu Tran, Chao Peng, Qingyang Lei, Haiming Qin, Lu Yang, Yi Zhang, Dongbo Bu, Ming Li

This paper introduces ProTCR, a reinforcement learning method for predicting TCR-pMHC binding, achieving higher accuracy than existing methods on benchmark datasets.

bioRxiv · Jan 5, 2026 · PreprintBioinformatics

Discovering and Validating Neoantigens by Mass Spectrometry-based Immunopeptidomics and Deep Learning

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, , Ming Li

This study introduces DeepNovo Peptidome and DeepSelf for neoantigen discovery and validation using immunopeptidomics and deep learning, demonstrating their application in cervical cancer tissues.

bioRxiv · Jul 5, 2022 · PreprintBioinformatics