Richard Van

556 total citations
16 papers, 269 citations indexed

About

Richard Van is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Materials Chemistry. According to data from OpenAlex, Richard Van has authored 16 papers receiving a total of 269 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 5 papers in Cellular and Molecular Neuroscience and 4 papers in Materials Chemistry. Recurrent topics in Richard Van's work include Protein Structure and Dynamics (5 papers), Neuroscience and Neuropharmacology Research (4 papers) and Machine Learning in Materials Science (3 papers). Richard Van is often cited by papers focused on Protein Structure and Dynamics (5 papers), Neuroscience and Neuropharmacology Research (4 papers) and Machine Learning in Materials Science (3 papers). Richard Van collaborates with scholars based in United States, China and Japan. Richard Van's co-authors include Yihan Shao, Xiaoliang Pan, Jingzhi Pu, Ye Mei, Kwangho Nam, Evgeny Epifanovsky, Biyue Zhu, Junming Ho, Can Zhang and Jing Huang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and The Journal of Physical Chemistry B.

In The Last Decade

Richard Van

13 papers receiving 268 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Richard Van United States	7	144	133	65	61	36	16	269
Konstantin Röder United Kingdom	12	282 2.0×	103 0.8×	30 0.5×	16 0.3×	52 1.4×	24	398
Ekaterina D. Kots Russia	10	191 1.3×	74 0.6×	73 1.1×	22 0.4×	67 1.9×	23	373
George A. Pantelopulos United States	12	341 2.4×	62 0.5×	26 0.4×	33 0.5×	80 2.2×	21	433
Fahimeh Baftizadeh United States	8	260 1.8×	115 0.9×	30 0.5×	16 0.3×	42 1.2×	11	356
Xiangda Peng China	10	229 1.6×	55 0.4×	25 0.4×	15 0.2×	54 1.5×	24	273
André A. S. T. Ribeiro Brazil	7	212 1.5×	72 0.5×	76 1.2×	24 0.4×	48 1.3×	12	346
Sara Bologna Italy	9	191 1.3×	73 0.5×	18 0.3×	24 0.4×	15 0.4×	11	292
Yanan Zhao China	9	195 1.4×	65 0.5×	18 0.3×	227 3.7×	74 2.1×	20	474
Payal Chatterjee United States	11	196 1.4×	48 0.4×	63 1.0×	13 0.2×	48 1.3×	20	315
Tatiana Miti United States	7	328 2.3×	73 0.5×	28 0.4×	45 0.7×	37 1.0×	9	468

Countries citing papers authored by Richard Van

Since Specialization

Citations

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

Fields of papers citing papers by Richard Van

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Richard Van

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

All Works

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16 of 16 papers shown

Liu, Zhenhua, Richard Van, Huizhe Wang, et al.. (2026). Highly sensitive chemiluminescence imaging of misfolded proteins in neurodegenerative models. Proceedings of the National Academy of Sciences. 123(2). e2513311123–e2513311123.

Rong, Jian, Chunyu Zhao, Richard Van, et al.. (2025). Development of a Novel ¹⁸F-Labeled Radioligand for Imaging Phosphodiesterase 7 with Positron Emission Tomography. Molecular Pharmaceutics. 22(3). 1657–1666.

Van, Richard, Xiaoliang Pan, Jin Liu, et al.. (2024). Exploring CRISPR-Cas9 HNH-Domain-Catalyzed DNA Cleavage Using Accelerated Quantum Mechanical Molecular Mechanical Free Energy Simulation. Biochemistry. 64(1). 289–299. 3 indexed citations

Li, Yinlong, Kenneth Dahl, Peter Johnström, et al.. (2024). Radiosynthesis and Evaluation of 11C-Labeled Isoindolone-Based Positive Allosteric Modulators for Positron Emission Tomography Imaging of Metabotropic Glutamate Receptor 2. ACS Pharmacology & Translational Science. 7(8). 2414–2423.

Ding, Weihua, Richard Van, Liuyue Yang, et al.. (2023). In vivo three-dimensional brain imaging with chemiluminescence probes in Alzheimer’s disease models. Proceedings of the National Academy of Sciences. 120(50). e2310131120–e2310131120. 19 indexed citations

Pan, Xiaoliang, Richard Van, Yuezhi Mao, et al.. (2023). Training machine learning potentials for reactive systems: A Colab tutorial on basic models. Journal of Computational Chemistry. 45(10). 638–647. 4 indexed citations

Pan, Xiaoliang, Richard Van, Jingzhi Pu, et al.. (2023). Free Energy Profile Decomposition Analysis for QM/MM Simulations of Enzymatic Reactions. Journal of Chemical Theory and Computation. 19(22). 8234–8244. 7 indexed citations

Van, Richard, Xiaoliang Pan, Ji Hwan Park, et al.. (2023). Machine learning based implicit solvent model for aqueous-solution alanine dipeptide molecular dynamics simulations. RSC Advances. 13(7). 4565–4577. 23 indexed citations

MacCuaig, William M., Richard Van, Megan R. Lerner, et al.. (2023). Influence of structural moieties in squaraine dyes on optoacoustic signal shape and intensity. Chem. 10(2). 713–729. 7 indexed citations

10.

Pan, Xiaoliang, Richard Van, Evgeny Epifanovsky, et al.. (2022). Accelerating Ab Initio Quantum Mechanical and Molecular Mechanical (QM/MM) Molecular Dynamics Simulations with Multiple Time Step Integration and a Recalibrated Semiempirical QM/MM Hamiltonian. The Journal of Physical Chemistry B. 126(23). 4226–4235. 13 indexed citations

11.

Pan, Xiaoliang, Junjie Yang, Richard Van, et al.. (2021). Machine-Learning-Assisted Free Energy Simulation of Solution-Phase and Enzyme Reactions. Journal of Chemical Theory and Computation. 17(9). 5745–5758. 85 indexed citations

12.

Deng, Xiaoyun, Fernando Salgado-Polo, Tuo Shao, et al.. (2021). Imaging Autotaxin In Vivo with ¹⁸F-Labeled Positron Emission Tomography Ligands. Journal of Medicinal Chemistry. 64(20). 15053–15068. 4 indexed citations

13.

Haider, Ahmed, Zhiwei Xiao, Xiaotian Xia, et al.. (2021). Development of a triazolobenzodiazepine-based PET probe for subtype-selective vasopressin 1A receptor imaging. Pharmacological Research. 173. 105886–105886. 2 indexed citations

14.

Yamasaki, Tomoteru, Xiaofei Zhang, Katsushi Kumata, et al.. (2020). Identification and Development of a New Positron Emission Tomography Ligand 4-(2-Fluoro-4-[¹¹C]methoxyphenyl)-5-((1-methyl-1H-pyrazol-3-yl)methoxy)picolinamide for Imaging Metabotropic Glutamate Receptor Subtype 2 (mGlu₂). Journal of Medicinal Chemistry. 63(20). 11469–11483. 4 indexed citations

15.

Deng, Xiaoyun, Yiding Zhang, Zhen Chen, et al.. (2020). Synthesis and preliminary evaluation of 4-hydroxy-6-(3-[11C]methoxyphenethyl)pyridazin-3(2H)-one, a 11C-labeled -amino acid oxidase (DAAO) inhibitor for PET imaging. Bioorganic & Medicinal Chemistry Letters. 30(16). 127326–127326. 4 indexed citations

16.

Yang, Jing, Wei Yin, Richard Van, et al.. (2020). Turn-on chemiluminescence probes and dual-amplification of signal for detection of amyloid beta species in vivo. Nature Communications. 11(1). 4052–4052. 94 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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