Chun Tang

7.2k total citations · 1 hit paper
113 papers, 5.1k citations indexed

About

Chun Tang is a scholar working on Molecular Biology, Materials Chemistry and Spectroscopy. According to data from OpenAlex, Chun Tang has authored 113 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Molecular Biology, 26 papers in Materials Chemistry and 22 papers in Spectroscopy. Recurrent topics in Chun Tang's work include Protein Structure and Dynamics (41 papers), Enzyme Structure and Function (21 papers) and Ubiquitin and proteasome pathways (11 papers). Chun Tang is often cited by papers focused on Protein Structure and Dynamics (41 papers), Enzyme Structure and Function (21 papers) and Ubiquitin and proteasome pathways (11 papers). Chun Tang collaborates with scholars based in China, United States and Poland. Chun Tang's co-authors include G. Marius Clore, Junji Iwahara, Zhou Gong, Michael F. Summers, Charles D. Schwieters, Zhu Liu, Tingting Zou, Ping Yin, Delin Zhang and Xiang Wang and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Chun Tang

106 papers receiving 5.1k citations

Hit Papers

Structural basis of N6-adenosine methylation by the METTL... 2016 2026 2019 2022 2016 250 500 750

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Chun Tang China 33 3.8k 829 803 695 616 113 5.1k
John D. Gross United States 37 3.6k 1.0× 526 0.6× 497 0.6× 726 1.0× 378 0.6× 75 5.0k
F.F. Vajdos United States 16 4.0k 1.1× 935 1.1× 675 0.8× 225 0.3× 578 0.9× 20 6.1k
Bernd Meyer Germany 29 3.7k 1.0× 170 0.2× 521 0.6× 816 1.2× 329 0.5× 83 5.3k
David Cowburn United States 53 7.7k 2.0× 318 0.4× 1.2k 1.5× 2.1k 3.0× 342 0.6× 180 10.4k
Ting Ran China 19 4.1k 1.1× 229 0.3× 706 0.9× 360 0.5× 511 0.8× 60 5.7k
Daniel H. Rich United States 48 4.6k 1.2× 320 0.4× 867 1.1× 340 0.5× 449 0.7× 287 8.3k
Elan Eisenmesser United States 30 3.3k 0.9× 171 0.2× 813 1.0× 487 0.7× 229 0.4× 76 4.5k
Irwin Chaiken United States 42 3.9k 1.0× 1.3k 1.5× 455 0.6× 544 0.8× 987 1.6× 221 6.6k
Tom Ellenberger United States 52 8.9k 2.4× 458 0.6× 597 0.7× 92 0.1× 751 1.2× 103 10.2k
Fritz Eckstein Germany 54 9.5k 2.5× 282 0.3× 588 0.7× 313 0.5× 913 1.5× 181 11.2k

Countries citing papers authored by Chun Tang

Since Specialization
Citations

This map shows the geographic impact of Chun Tang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chun Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chun Tang more than expected).

Fields of papers citing papers by Chun Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chun Tang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chun Tang. The network helps show where Chun Tang may publish in the future.

Co-authorship network of co-authors of Chun Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Chun Tang. A scholar is included among the top collaborators of Chun Tang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chun Tang. Chun Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
2.
Zhang, Yating, Jie Liu, Hanzhi Liang, et al.. (2025). An adoptive cell therapy with TREM2‐overexpressing macrophages mitigates the transition from acute kidney injury to chronic kidney disease. Clinical and Translational Medicine. 15(3). e70252–e70252. 5 indexed citations
3.
Wang, Xianwei, Haichuan Zhu, Zhou Gong, et al.. (2025). Small-Molecule Inhibitors of Transcription Factor PU.1 for the Treatment of Acute T Cell Lymphoblastic Leukemia and Organ Fibrosis. CCS Chemistry. 8(1). 319–340.
4.
Wang, Tong, Yun‐Bi Lu, Cong Chen, et al.. (2025). PINK1 deficiency permits the development of Lewy body dementia with coexisting Aβ pathology. Alzheimer s & Dementia. 21(9). e70730–e70730. 1 indexed citations
5.
Kang, Yan, Guo Li, Qing Li, et al.. (2024). Association of clopidogrel resistance and ABCD-GENE score with long-term clinical prognosis in patients with ischemic stroke or TIA. Revue Neurologique. 180(7). 682–688. 1 indexed citations
7.
Song, Bin, Wen‐Ting Chu, Dong Xu, et al.. (2024). Connecting Protein Millisecond Conformational Dynamics to Protein Thermal Stability. SHILAP Revista de lepidopterología. 4(8). 3310–3320. 2 indexed citations
8.
Zhang, Xinghe, et al.. (2024). Dissecting diazirine photo-reaction mechanism for protein residue-specific cross-linking and distance mapping. Nature Communications. 15(1). 6060–6060. 15 indexed citations
9.
Zhao, Nan, Huajian Gao, Weijie Zhang, et al.. (2024). Spatially resolved profiling of protein conformation and interactions by biocompatible chemical cross-linking in living cells. Nature Communications. 15(1). 8331–8331. 4 indexed citations
10.
Zhu, Ting, Yiqing Zhang, Zeyu Zhang, et al.. (2023). The role of microbial metabolites in diabetic kidney disease. Heliyon. 9(7). e17844–e17844. 7 indexed citations
11.
Lu, Yunpeng, Kai Ye, Zihan Li, et al.. (2023). Regulating polystyrene glass transition temperature by varying the hydration levels of aromatic ring/Li+ interaction. Physical Chemistry Chemical Physics. 25(44). 30223–30227. 2 indexed citations
12.
Fu, Weitao, Hao Yang, Zhou Gong, et al.. (2023). Small-Molecule Inhibition of Androgen Receptor Dimerization as a Strategy against Prostate Cancer. ACS Central Science. 9(4). 675–684. 12 indexed citations
13.
Fu, Rong, Qingyu Zhao, Han Han, et al.. (2023). A Chiral Emissive Conjugated Corral for High‐Affinity and Highly Enantioselective Recognition in Water. Angewandte Chemie International Edition. 62(51). e202315990–e202315990. 50 indexed citations
14.
Tang, Chun, et al.. (2023). Effects of Mass Change on Liquid–Liquid Phase Separation of the RNA-Binding Protein Fused in Sarcoma. Biomolecules. 13(4). 625–625. 2 indexed citations
15.
Tang, Yuliang, Zhou Gong, Rohit Jain, et al.. (2022). Characterization of protein unfolding by fast cross-linking mass spectrometry using di-ortho-phthalaldehyde cross-linkers. Nature Communications. 13(1). 39 indexed citations
16.
Gong, Zhou, Dong Xu, Shu-Qun Liu, et al.. (2022). Fast cross-linking by DOPA2 promotes the capturing of a stereospecific protein complex over nonspecific encounter complexes. Biophysics Reports. 8(5-6). 239–252. 5 indexed citations
17.
18.
Wang, Yong, Chun Tang, Erkang Wang, & Jin Wang. (2012). Exploration of Multi-State Conformational Dynamics and Underlying Global Functional Landscape of Maltose Binding Protein. PLoS Computational Biology. 8(4). e1002471–e1002471. 47 indexed citations
19.
Tang, Chun, et al.. (2008). Replica exchange simulations of transient encounter complexes in protein–protein association. Proceedings of the National Academy of Sciences. 105(35). 12855–12860. 91 indexed citations
20.
Tang, Chun, Erin Loeliger, Paz J. Luncsford, et al.. (2003). Entropic switch regulates myristate exposure in the HIV-1 matrix protein. Proceedings of the National Academy of Sciences. 101(2). 517–522. 258 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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