Author

Charles Zheng

University of PennsylvaniaORCID 0009-0008-7656-9216Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:benchmarking· 2 Research Focus:differential expression· 2 Research Focus:gene regulatory network inference· 2 Approach:machine learning (classical)· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1

Frequent Co-Authors

Li SheniD· 3 shared Dokyoon KimiD· 2 shared Tianhua ZhaiiD· 2 shared Anyu PaniD· 1 shared Fangyuan ZhangiD· 1 shared Jonghyun LeeiD· 1 shared Manu ShivakumariD· 1 shared

Activity by Year

2026-2026 · peak 3/yr

Co-Author Collaboration Network

7 top collaborators · 14 mutual co-author links

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3 shared papersBioinformatics

Li ShenORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintOct 20, 2026

Integrating Multisource Target Evidence with Machine-Learning Potency Prediction for Alzheimer's Disease Drug Discovery

Anyu Pan, Tianhua Zhai, Jonghyun Lee…·Li Shen

The paper develops a platform integrating multisource target evidence with machine learning for Alzheimer's drug discovery, improving potency prediction and model performance.

DOI 10.64898/2026.10.14.759026

humanmachine learning (classical)

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Genetic & Genomic MedicinemedRxivPreprintAug 27, 2026

Absorption and Co-expression Modules Show Where Polygenic and Proteomic Risk Scores Diverge in Neurodegenerative Diseases

Charles Zheng, Manu Shivakumar, Li Shen, Dokyoon Kim

The paper quantifies the divergence between polygenic and proteomic risk scores in neurodegenerative diseases by analyzing absorption and co-expression modules across multiple cohorts.

DOI 10.64898/2026.08.24.26361271

humanproteomics

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BioinformaticsbioRxivPreprintJul 14, 2026

Integrative single-nucleus multi-omics profiling identifies candidate regulators and signaling axes in Alzheimer's disease lipid-processing microglia

Charles Zheng, Tianhua Zhai, Fangyuan Zhang, Li Shen

The paper identifies candidate regulators and signaling axes in Alzheimer's disease lipid-processing microglia through multi-omics analysis across multiple cohorts.

DOI 10.64898/2026.07.10.737805

humanscRNA-seq

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