Author

Q. C. Zhang

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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Microbiology· 2 Cell Biology· 1 Immunology· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 3 Organism:human· 3 Assay:bulk RNA-seq· 2 Research Focus:cell type annotation· 2 Research Focus:drug response / drug discovery· 2 Research Focus:cell signaling & trafficking· 1 Assay:ChIP-seq· 1 Approach:deep learning· 1

Frequent Co-Authors

M. Gong· 2 shared Q. Ding· 2 shared W. Huang· 2 shared X. Ju· 2 shared B. Zhang· 1 shared C. Li· 1 shared H. Jiang· 1 shared H. Liu· 1 shared

Activity by Year

2020-2021 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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2 shared papersMicrobiology

M. Gong

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Analysis of viral RNA-host protein interactomes enables rapid antiviral drug discovery

S. Zhang, W. Huang, L. Ren, X. Ju, M. Gong, J. Rao, L. Sun, P. Li, Q. Ding, J. Wang, Q. C. Zhang

The paper identifies antiviral drugs by analyzing RNA-host protein interactomes of SARS-CoV-2, EBOV, and ZIKV.

bioRxiv · Apr 25, 2021 · PreprintMicrobiology

A novel cell culture system modeling the SARS-CoV-2 life cycle

X. Ju, Y. Zhu, Y. Wang, J. Li, J. Zhang, M. Gong, W. Ren, S. Li, J. Zhong, Q. C. Zhang, R. Zhang, Q. Ding

This paper develops a BSL-2 cell culture system for producing SARS-CoV-2 virus-like particles to enable safe antiviral screening and life cycle studies.

bioRxiv · Dec 13, 2020Microbiology

CD127 imprints functional heterogeneity to diversify monocyte responses in human inflammatory diseases

B. Zhang, Y. Zhang, L. Xiong, Y. Li, Y. Zhang, J. Zhao, H. Jiang, C. Li, Y. Liu, X. Liu, H. Liu, Y.-F. Ping, Q. C. Zhang, Z. Zhang, X.-W. Bian, , X. Hu

The paper identifies a CD127-expressing monocyte subset, M127, associated with anti-inflammatory properties in inflammatory diseases and correlates its expansion with milder COVID-19 outcomes.

bioRxiv · Nov 10, 2020Immunology

Predicting dynamic cellular protein-RNA interactions using deep learning and in vivo RNA structure

L. Sun, K. Xu, W. Huang, Y. Yang, L. Tang, T. Xiong, Q. C. Zhang

This paper introduces PrismNet, a deep learning model that uses in vivo RNA structures to predict protein-RNA interactions and identifies disease-associated mutations affecting these interactions.

bioRxiv · May 5, 2020Cell Biology