Author

Ke Deng

Tsinghua UniversityORCID 0000-0002-4383-8319Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:differential expression· 2 Assay:ATAC-seq· 1 Research Focus:batch correction / integration· 1 Assay:bulk RNA-seq· 1 Research Focus:dimensionality reduction· 1 Assay:DNA methylation· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

Alfonso UrbanucciiD· 1 shared Alma Vuori· 1 shared Barbara La FerlaiD· 1 shared Barbara ZerbatoiD· 1 shared Chongzhi ZangiD· 1 shared Cinzia BragatoiD· 1 shared Ciro Leonardo PierriiD· 1 shared Clifford A. MeyeriD· 1 shared

Activity by Year

2018-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperCancer Biology

Alfonso UrbanucciORCID

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3 papers

Recent·Most cited

Cancer BiologybioRxivPreprintSep 1, 2026

PGM3 inhibition rewires RUVBL2-dependent DNA repair and induces a BRCAness-like state in pancreatic cancer cells

Barbara Zerbato, Gabriele Taverna, Marina La Chimia…·Ferdinando Chiaradonna

This study shows that inhibiting PGM3 in pancreatic cancer cells disrupts DNA repair pathways, induces a BRCAness-like state, and increases sensitivity to PARP inhibitors and radiation.

DOI 10.64898/2026.08.31.746486

humanbulk RNA-seq

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BioinformaticsbioRxivPreprintOct 22, 2021

Accurate estimation of intrinsic biases for improved analysis of bulk and single-cell chromatin accessibility sequencing data using SELMA

Shengen Shawn Hu, Lin L. Liu, Qi Li…·Chongzhi Zang

SELMA estimates intrinsic cleavage biases in bulk and single-cell chromatin accessibility data, improving analysis accuracy and cell clustering in single-cell ATAC-seq.

3 citations

ATAC-seqDNA methylation

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BioinformaticsBioinformaticsPeer-reviewedApr 20, 2018

DEsingle for detecting three types of differential expression in single-cell RNA-seq data

Zhun Miao, Ke Deng, Xiaowo Wang, Xuegong Zhang

DEsingle identifies three types of differential expression in single-cell RNA-seq by distinguishing real and dropout zeros using a Zero-Inflated Negative Binomial model.

272 citationstop 1%

scRNA-seqstatistical model

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