Author

Sheng Zhao

BeiGene (China)ORCID 0000-0002-3356-9100Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Sheng Zhao1 paper · Innovative Genomics Institute

Biology Disciplines

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Bioengineering· 1 Cell Biology· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 3 Research Focus:drug response / drug discovery· 2 Organism:human· 2 Assay:multiome· 2 Assay:bulk RNA-seq· 1 Research Focus:gene regulatory network inference· 1 Organism:mouse· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Ana Martín-VillalbaiD· 1 shared Brian A. SiemonsiD· 1 shared Bruce R. ConkliniD· 1 shared Chuanqing TangiD· 1 shared Damian WollnyiD· 1 shared Deepak SrivastavaiD· 1 shared Gabriel NeimaniD· 1 shared Hesong HaniD· 1 shared

Activity by Year

2016-2025 · peak 2/yr

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10 top collaborators · 17 mutual co-author links

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1 shared paperGenomics

Ana Martín-VillalbaORCID

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3 papers

Recent·Most cited

Intracellular auto-circularizing RNA using human tRNA splicing elements

Qianbo Ma, Chuanqing Tang, Jie Wang, Yingchun Liu, Xiulian Sun, Sheng Zhao

This study identifies human tRNA splicing elements that enable efficient intracellular auto-circularization of RNA, providing a framework for circRNA production.

bioRxiv · Jul 28, 2025 · PreprintCell Biology

A cardiac microphysiological system for screening lipid nanoparticle/mRNA complexes predicts in vivo efficacy for heart transfection

Gabriel Neiman, Mauro W. Costa, Hesong Han, Sheng Zhao, Tammy Ng, Brian A. Siemons, Tomohiro Nishino, Yu Huang, Shyam Lal Jinagal, Kenneth Kun-yu Wu, Luke M. Judge, Bruce R. Conklin, Deepak Srivastava, Niren Murthy, Kevin E. Healy

The paper develops a cardiac microphysiological system to screen lipid nanoparticle/mRNA complexes and identifies a formulation with improved transfection efficiency and reduced off-target liver uptake.

bioRxiv · Mar 7, 2025 · PreprintBioengineering

RNA-seq library preparation from single pancreatic acinar cells

Damian Wollny, Sheng Zhao, Ana Martín-Villalba

The paper develops a protocol for single-cell RNA sequencing of pancreatic acinar cells, which have high ribonuclease content, achieving high-quality libraries with 5x106 reads per cell and 80% transcript mapping rate.

bioRxiv · Nov 4, 2016 · PreprintGenomics