Author

Peng Cheng

Beijing Institute of Microbiology and Epidemiology

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

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Biology Disciplines

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Bioinformatics· 2 Biochemistry· 1 Immunology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:deep learning· 2 Organism:human· 2 Approach:benchmark study· 1 Research Focus:cell type annotation· 1 Research Focus:database / resource· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1

Frequent Co-Authors

Aidan Dunleavy· 1 shared Aidan NeheriD· 1 shared Aixin Li· 1 shared Anna KonstorumiD· 1 shared Aparna SrinivasaniD· 1 shared Barry J. GrantiD· 1 shared Bhargob Kakoty· 1 shared Bin-Bin Fang· 1 shared

Activity by Year

2018-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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1 shared paperImmunology

Aidan Dunleavy

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Author profile →

4 papers

Recent·Most cited

Putting computational models of immunity to the test - an invited challenge to predict B. pertussis vaccination outcomes

Pramod S. Shinde, Lisa Willemsen, Michael Anderson, Minori Aoki, Saonli Basu, Julie G. Burel, Peng Cheng, Souradipto Ghosh Dastidar, Aidan Dunleavy, Tal Einav, Jamie Forschmiedt, Slim Fourati, Javier Garcia, William Gibson, Jason A Greenbaum, , Bjoern Peters

The paper benchmarks 49 algorithms for predicting B. pertussis vaccination outcomes, finding that purpose-built models outperform literature-based ones due to better handling of nonlinearities and data preprocessing.

PLoS Computational Biology · Mar 31, 2025Peer-reviewedImmunology

A natural language processing system for the efficient extraction of cell markers

Peng Cheng, Yan Peng, Xiaoling Zhang, Sheng Chen, Bin-Bin Fang, Yan-Ze Li, Yimin Sun

This study develops MarkerGeneBERT, an NLP system that extracts cell markers from scRNA-seq literature, achieving 76% completeness and 75% accuracy in marker gene identification.

Scientific Reports · Sep 11, 2024Peer-reviewedBioinformatics

Exploring the Knowledge of An Outstanding Protein to Protein Interaction Transformer

Sen Yang, Dawei Feng, Peng Cheng, Yang Liu, Shengqi Wang

This paper introduces PPITrans, a Transformer-based model for protein-protein interaction prediction that outperforms existing methods on unseen species.

IEEE Transactions on Computational Biology and Bioinformatics · Mar 27, 2024Peer-reviewedBioinformatics

Improved performance of microbial fuel cells through addition of trehalose lipids

Peng Cheng, Rui Shan, Hao-Ran Yuan, Ge Dong, Li-fang Deng, Yong Chen

This paper adds trehalose lipid to microbial fuel cells (MFCs) to enhance power output by improving electron transfer and reducing internal resistance.

bioRxiv · Jun 5, 2018 · PreprintBiochemistry