Kunqian Yu

2.1k total citations
56 papers, 1.4k citations indexed

About

Kunqian Yu is a scholar working on Molecular Biology, Materials Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Kunqian Yu has authored 56 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Molecular Biology, 11 papers in Materials Chemistry and 7 papers in Computational Theory and Mathematics. Recurrent topics in Kunqian Yu's work include Computational Drug Discovery Methods (7 papers), Protein Structure and Dynamics (6 papers) and Luminescence and Fluorescent Materials (6 papers). Kunqian Yu is often cited by papers focused on Computational Drug Discovery Methods (7 papers), Protein Structure and Dynamics (6 papers) and Luminescence and Fluorescent Materials (6 papers). Kunqian Yu collaborates with scholars based in China, United States and United Kingdom. Kunqian Yu's co-authors include Hualiang Jiang, Weiliang Zhu, Kaixian Chen, Xiaomin Luo, Cheng Luo, Wenbin Zeng, Honglin Li, Mingyue Zheng, Hui Li and Wei Fu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and PLoS ONE.

In The Last Decade

Kunqian Yu

54 papers receiving 1.4k citations

Peers

Kunqian Yu

CTM

Shu-Qun Liu China

M. Yu. Lobanov Russia

Kellon Belfon United States

Gregory A. Ross United States

Miguel X. Fernandes Spain

Lauren Raguette United States

Boris Aguilar United States

Linda Y. Zhang United States

Gianluca Degliesposti United Kingdom

Brian Y. Feng United States

Shu-Qun Liu China

Kunqian Yu

1.3k ×1.5

361 ×1.1

CTM

228 ×1.1

255 ×1.3

203 ×1.4

Citations per year, relative to Kunqian Yu Kunqian Yu (= 1×) peers Shu-Qun Liu

Countries citing papers authored by Kunqian Yu

Since Specialization

Citations

This map shows the geographic impact of Kunqian Yu'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 Kunqian Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kunqian Yu more than expected).

Fields of papers citing papers by Kunqian Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kunqian Yu. 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 Kunqian Yu. The network helps show where Kunqian Yu may publish in the future.

Co-authorship network of co-authors of Kunqian Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Kunqian Yu. A scholar is included among the top collaborators of Kunqian Yu 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 Kunqian Yu. Kunqian Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Ma, Yeshuo, et al.. (2024). Integrated computational approaches for advancing antimicrobial peptide development. Trends in Pharmacological Sciences. 45(11). 1046–1060. 3 indexed citations

Huang, Shuai, Bin Feng, Xiang Cheng, et al.. (2023). Controlling ESIPT-based AIE effects for designing optical materials with single-component white-light emission. Chemical Engineering Journal. 476. 146436–146436. 20 indexed citations

Zhang, Baohua, Hui Li, Kunqian Yu, & Zhong Jin. (2022). Molecular docking-based computational platform for high-throughput virtual screening. PubMed. 4(1). 63–74. 64 indexed citations

Li, Zhe, Hui Li, Kunqian Yu, & Hai‐Bin Luo. (2021). Perspective of drug design with high-performance computing. National Science Review. 8(12). nwab105–nwab105. 3 indexed citations

Li, Zhe, Xin Li, Yi-You Huang, et al.. (2020). Identify potent SARS-CoV-2 main protease inhibitors via accelerated free energy perturbation-based virtual screening of existing drugs. Proceedings of the National Academy of Sciences. 117(44). 27381–27387. 177 indexed citations

Liu, Tingting, Teng Yang, Kaixian Chen, et al.. (2019). The inhibitory mechanism of aurintricarboxylic acid targeting serine/threonine phosphatase Stp1 in Staphylococcus aureus: insights from molecular dynamics simulations. Acta Pharmacologica Sinica. 40(6). 850–858. 10 indexed citations

Liu, Shien, Junchi Hu, Hao Zhang, et al.. (2017). Conformation and dynamics of the C-terminal region in human phosphoglycerate mutase 1. Acta Pharmacologica Sinica. 38(12). 1673–1682. 10 indexed citations

Lu, Junyan, Chenxiao Jiang, Xiaojing Li, et al.. (2015). A gating mechanism for Pi release governs the mRNA unwinding by eIF4AI during translation initiation. Nucleic Acids Research. 43(21). gkv1033–gkv1033. 5 indexed citations

Zhang, Yu, Lei Xu, Zhiqiang Zhang, et al.. (2015). Structure–Activity Relationships and Anti-inflammatory Activities of N-Carbamothioylformamide Analogues as MIF Tautomerase Inhibitors. Journal of Chemical Information and Modeling. 55(9). 1994–2004. 6 indexed citations

10.

Zhong, Bing, Guangrong Qin, Huaiyu Yang, et al.. (2014). Progress in Studies of Structure, Mechanism and Antagonists Interaction of GPCR Co-Receptors for HIV. Current Pharmaceutical Biotechnology. 15(10). 938–950. 1 indexed citations

11.

Qin, Guangrong, et al.. (2014). Exploring the RING-Catalyzed Ubiquitin Transfer Mechanism by MD and QM/MM Calculations. PLoS ONE. 9(7). e101663–e101663. 12 indexed citations

12.

Cui, Meng, Guangrong Qin, Kunqian Yu, M. Scott Bowers, & Miao Zhang. (2014). Targeting the Small- and Intermediate-Conductance Ca<sup>2+</sup>-Activated Potassium Channels: The Drug-Binding Pocket at the Channel/Calmodulin Interface. Neurosignals. 22(2). 65–78. 17 indexed citations

13.

Zhu, Kongkai, Junyan Lu, Fei Ye, et al.. (2013). Structure-based computational study of the hydrolysis of New Delhi metallo-β-lactmase-1. Biochemical and Biophysical Research Communications. 431(1). 2–7. 13 indexed citations

14.

Yang, Huaiyu, Zhaobing Gao, Ping Li, et al.. (2012). A Theoretical Model for Calculating Voltage Sensitivity of Ion Channels and the Application on Kv1.2 Potassium Channel. Biophysical Journal. 102(8). 1815–1825. 2 indexed citations

15.

Yu, Kunqian. (2009). DDGrid:A Grid with Massive Drug Virtual-Screening Support. Computer Engineering and Science. 2 indexed citations

16.

Zhang, Jian, Kunqian Yu, Weiliang Zhu, & Hualiang Jiang. (2006). Neuraminidase pharmacophore model derived from diverse classes of inhibitors. Bioorganic & Medicinal Chemistry Letters. 16(11). 3009–3014. 30 indexed citations

17.

Han, Cong, Lirui Wang, Kunqian Yu, et al.. (2006). Biochemical characterization and inhibitor discovery of shikimate dehydrogenase from Helicobacter pylori. FEBS Journal. 273(20). 4682–4692. 58 indexed citations

18.

Zheng, Mingyue, Kunqian Yu, Hong Liu, et al.. (2006). QSAR analyses on avian influenza virus neuraminidase inhibitors using CoMFA, CoMSIA, and HQSAR. Journal of Computer-Aided Molecular Design. 20(9). 549–566. 19 indexed citations

19.

Wang, Feng, Kunqian Yu, Jing Chen, et al.. (2005). Novel cyclophilin D inhibitors derived from quinoxaline exhibit highly inhibitory activity against rat mitochondrial swelling and Ca2+ uptake/release. Acta Pharmacologica Sinica. 26(10). 1201–1211. 40 indexed citations

20.

Yu, Kunqian, Wei Fu, Hong Liu, et al.. (2004). Computational Simulations of Interactions of Scorpion Toxins with the Voltage-Gated Potassium Ion Channel. Biophysical Journal. 86(6). 3542–3555. 48 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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