Author

Qun Liu

Brookhaven National Laboratory

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· 1 Developmental Biology· 1 Molecular Biology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Research Focus:cell type annotation· 1 Approach:experimental assay· 1 Organism:fungi (other)· 1 Research Focus:gene regulatory network inference· 1 Organism:plant (other)· 1 Assay:protein structure· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

An ZengiD· 1 shared Gang PeiiD· 1 shared Guangyi FaniD· 1 shared Hanbo LiiD· 1 shared He Zhang· 1 shared Hongwei Pan· 1 shared Huanming YangiD· 1 shared İvet BahariD· 1 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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1 shared paperDevelopmental Biology

An ZengORCID

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3 papers

Recent·Most cited

Cell Type Architecture and Positional Gene Gradients in an Adult Animal at Subcellular Resolution

Maoqin Sun, Yuxiaofei Wang, Kai Han, Lidong Guo, Yuehua Chen, Yao Li, Yaru Lin, Xiawei Liu, Zhi Huang, Qun Liu, Wenjie Guo, Rui Zhang, Wandong Zhao, Langchao Liang, Xiaoyu Wei, , An Zeng

This study reconstructs 3D spatial transcriptomic models of planarians to map cell type distribution and positional gene regulation, identifying candidate genes involved in regeneration.

bioRxiv · Feb 20, 2026 · PreprintDevelopmental Biology

Substrate binding and channeling allosterically modulate the interactions within the AlkB-AlkG electron transfer complex

Karolina Mikulska‐Ruminska, Matthew Licht, Mehmed Z. Ertem, John Shanklin, Qun Liu, İvet Bahar

This study investigates the dynamics and interactions of the AlkB-AlkG electron transfer complex using computational methods, revealing how substrate binding and channeling modulate allosteric effects and electron transfer efficiency.

bioRxiv · Jun 23, 2025 · PreprintMolecular Biology

Predicting metal-binding proteins and structures through integration of evolutionary-scale and physics-based modeling

Xin Dai, Max Henderson, Shinjae Yoo, Qun Liu

The paper develops ESMBind, a workflow combining evolutionary and physics-based modeling to predict metal-binding proteins and their structures, showing improved performance over existing methods.

Journal of Molecular Biology · Mar 1, 2025Peer-reviewedBioinformatics