Wenbo Yu

4.7k total citations · 2 hit papers
100 papers, 3.4k citations indexed

About

Wenbo Yu is a scholar working on Molecular Biology, Organic Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Wenbo Yu has authored 100 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Molecular Biology, 37 papers in Organic Chemistry and 27 papers in Computational Theory and Mathematics. Recurrent topics in Wenbo Yu's work include Computational Drug Discovery Methods (27 papers), Protein Structure and Dynamics (21 papers) and Synthesis and biological activity (14 papers). Wenbo Yu is often cited by papers focused on Computational Drug Discovery Methods (27 papers), Protein Structure and Dynamics (21 papers) and Synthesis and biological activity (14 papers). Wenbo Yu collaborates with scholars based in United States, China and Nepal. Wenbo Yu's co-authors include Alexander D. MacKerell, Kenno Vanommeslaeghe, Xibing He, E. Prabhu Raman, Sirish Kaushik Lakkaraju, Zijing Lin, Zhijian Huang, Chao Shen, Pengfei Zhang and Fengtian Xue and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and The Journal of Chemical Physics.

In The Last Decade

Wenbo Yu

93 papers receiving 3.4k citations

Hit Papers

Extension of the CHARMM general force field to sulfonyl‐c... 2012 2026 2016 2021 2012 2016 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wenbo Yu United States 30 1.9k 822 819 390 377 100 3.4k
Jennifer L. Knight United States 16 2.2k 1.2× 682 0.8× 878 1.1× 246 0.6× 328 0.9× 23 3.5k
Thomas E. Exner Germany 29 1.8k 1.0× 609 0.7× 930 1.1× 439 1.1× 348 0.9× 93 3.3k
David S. Cerutti United States 16 2.3k 1.2× 656 0.8× 820 1.0× 283 0.7× 393 1.0× 28 3.7k
Felice C. Lightstone United States 32 2.2k 1.2× 733 0.9× 661 0.8× 282 0.7× 463 1.2× 105 3.9k
Yixiang Cao United States 14 1.5k 0.8× 687 0.8× 597 0.7× 241 0.6× 453 1.2× 23 3.1k
Goran Krilov United States 19 2.1k 1.1× 771 0.9× 948 1.2× 250 0.6× 544 1.4× 38 3.9k
Alpeshkumar K. Malde Australia 22 1.7k 0.9× 1.1k 1.3× 600 0.7× 276 0.7× 304 0.8× 65 3.8k
Erin M. Duffy United States 22 1.2k 0.7× 765 0.9× 607 0.7× 452 1.2× 471 1.2× 36 3.0k
Markus A. Lill United States 29 1.9k 1.0× 550 0.7× 1.3k 1.6× 258 0.7× 230 0.6× 93 3.3k
Kyoung Tai No South Korea 33 1.3k 0.7× 549 0.7× 723 0.9× 553 1.4× 384 1.0× 167 3.1k

Countries citing papers authored by Wenbo Yu

Since Specialization
Citations

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

Fields of papers citing papers by Wenbo Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wenbo Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Wenbo Yu. A scholar is included among the top collaborators of Wenbo 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 Wenbo Yu. Wenbo Yu 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
1.
Kumar, Anmol, et al.. (2025). Increasing the Accuracy and Robustness of the CHARMM General Force Field with an Expanded Training Set. Journal of Chemical Theory and Computation. 21(6). 3044–3065. 6 indexed citations
2.
Zhao, Mingtian, Wenbo Yu, & Alexander D. MacKerell. (2024). Enhancing SILCS-MC via GPU Acceleration and Ligand Conformational Optimization with Genetic and Parallel Tempering Algorithms. The Journal of Physical Chemistry B. 128(30). 7362–7375. 3 indexed citations
4.
Yu, Wenbo, et al.. (2023). Effects of Exogenous Auxin on Mesocotyl Elongation of Sorghum. Plants. 12(4). 944–944. 8 indexed citations
5.
Yu, Wenbo, et al.. (2023). Development of CHARMM additive potential energy parameters for α-methyl amino acids. Biophysical Journal. 122(3). 425a–425a. 1 indexed citations
6.
8.
Li, Shuaizhang, Jinghua Zhao, Ruili Huang, et al.. (2021). Profiling the Tox21 Chemical Collection for Acetylcholinesterase Inhibition. Environmental Health Perspectives. 129(4). 47008–47008. 29 indexed citations
9.
Yang, Lin, Tian-Jiao Chen, Fen Wang, et al.. (2020). Structures of β-glycosidase LXYL-P1-2 reveals the product binding state of GH3 family and a specific pocket for Taxol recognition. Communications Biology. 3(1). 22–22. 8 indexed citations
10.
MacKerell, Alexander D., et al.. (2020). Identification and characterization of fragment binding sites for allosteric ligand design using the site identification by ligand competitive saturation hotspots approach (SILCS-Hotspots). Biochimica et Biophysica Acta (BBA) - General Subjects. 1864(4). 129519–129519. 42 indexed citations
11.
Chauhan, Jay, et al.. (2020). <p>Optimization of a Benzothiazole Indolene Scaffold Targeting Bacterial Cell Wall Assembly</p>. Drug Design Development and Therapy. Volume 14. 567–574. 6 indexed citations
12.
Swaroop, Alok, Jon A. Oyer, Christine Will, et al.. (2018). An activating mutation of the NSD2 histone methyltransferase drives oncogenic reprogramming in acute lymphocytic leukemia. Oncogene. 38(5). 671–686. 36 indexed citations
13.
Cavalier, Michael C., Zephan Melville, E. Prabhu Raman, et al.. (2016). Novel protein–inhibitor interactions in site 3 of Ca2+-bound S100B as discovered by X-ray crystallography. Acta Crystallographica Section D Structural Biology. 72(6). 753–760. 11 indexed citations
14.
Yu, Wenbo, E. Prabhu Raman, Sirish Kaushik Lakkaraju, Lei Fang, & Alexander D. MacKerell. (2015). Pharmacophore Modeling using Site-Identification by Ligand Competitive Saturation (SILCS) Method with Multiple Probe Molecules. Biophysical Journal. 108(2). 12a–13a. 47 indexed citations
15.
Cheng, Haili, et al.. (2013). Cloning and Characterization of the Glycoside Hydrolases That Remove Xylosyl Groups from 7-β-xylosyl-10-deacetyltaxol and Its Analogues. Molecular & Cellular Proteomics. 12(8). 2236–2248. 37 indexed citations
16.
Varney, Kristen M., Alexandre M. J. J. Bonvin, Marzena Pazgier, et al.. (2013). Turning Defense into Offense: Defensin Mimetics as Novel Antibiotics Targeting Lipid II. PLoS Pathogens. 9(11). e1003732–e1003732. 50 indexed citations
17.
Yu, Wenbo, Xibing He, Kenno Vanommeslaeghe, & Alexander D. MacKerell. (2012). Extension of the CHARMM general force field to sulfonyl‐containing compounds and its utility in biomolecular simulations. Journal of Computational Chemistry. 33(31). 2451–2468. 716 indexed citations breakdown →
18.
Xu, Zhenghong, Ya‐Wen Chen, Aruna Battu, et al.. (2011). Targeting Zymogen Activation To Control the Matriptase-Prostasin Proteolytic Cascade. Journal of Medicinal Chemistry. 54(21). 7567–7578. 16 indexed citations
19.
Yu, Wenbo, et al.. (2009). Extensive conformational searches of 13 representative dipeptides and an efficient method for dipeptide structure determinations based on amino acid conformers. Journal of Computational Chemistry. 30(13). 2105–2121. 32 indexed citations
20.
Yu, Wenbo, Lei Liang, Zijing Lin, et al.. (2008). Comparison of some representative density functional theory and wave function theory methods for the studies of amino acids. Journal of Computational Chemistry. 30(4). 589–600. 61 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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