Lee‐Ping Wang

12.9k total citations · 8 hit papers
90 papers, 8.4k citations indexed

About

Lee‐Ping Wang is a scholar working on Atomic and Molecular Physics, and Optics, Molecular Biology and Materials Chemistry. According to data from OpenAlex, Lee‐Ping Wang has authored 90 papers receiving a total of 8.4k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Atomic and Molecular Physics, and Optics, 35 papers in Molecular Biology and 26 papers in Materials Chemistry. Recurrent topics in Lee‐Ping Wang's work include Protein Structure and Dynamics (25 papers), Spectroscopy and Quantum Chemical Studies (23 papers) and Advanced Chemical Physics Studies (21 papers). Lee‐Ping Wang is often cited by papers focused on Protein Structure and Dynamics (25 papers), Spectroscopy and Quantum Chemical Studies (23 papers) and Advanced Chemical Physics Studies (21 papers). Lee‐Ping Wang collaborates with scholars based in United States, United Kingdom and Germany. Lee‐Ping Wang's co-authors include Vijay S. Pande, Robert T. McGibbon, Kyle A. Beauchamp, Todd J. Martı́nez, Troy Van Voorhis, Jason Swails, Matthew P. Harrigan, John D. Chodera, Peter Eastman and Christoph Klein and has published in prestigious journals such as Chemical Reviews, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Lee‐Ping Wang

88 papers receiving 8.4k citations

Hit Papers

OpenMM 7: Rapid development of high performance algorith... 2012 2026 2016 2021 2017 2015 2012 2014 2014 500 1000 1.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. OpenMM 7: Rapid development of high performance algorithms for molecular dynamics
    2017 1.7k citations Peter Eastman, Jason Swails et al. PLoS Computational Biology profile →
  2. MDTraj: A Modern Open Library for the Analysis of Molecular Dynamics Trajectories
    2015 1.5k citations Robert T. McGibbon, Kyle A. Beauchamp et al. Biophysical Journal profile →
  3. OpenMM 4: A Reusable, Extensible, Hardware Independent Library for High Performance Molecular Simulation
    2012 540 citations Peter Eastman, John D. Chodera et al. Journal of Chemical Theory and Computation profile →
  4. Building Force Fields: An Automatic, Systematic, and Reproducible Approach
    2014 419 citations Lee‐Ping Wang, Todd J. Martı́nez et al. profile →
  5. Discovering chemistry with an ab initio nanoreactor
    2014 317 citations Lee‐Ping Wang, A.V. Titov et al. profile →
  6. TeraChem: A graphical processing unit‐accelerated electronic structure package for large‐scale ab initio molecular dynamics
    2020 215 citations Stefan Seritan, Christoph Bannwarth et al. Wiley Interdisciplinary Reviews Computational Molecular Science profile →
  7. Non-bonded force field model with advanced restrained electrostatic potential charges (RESP2)
    2020 197 citations Michael Schauperl, Paul S. Nerenberg et al. profile →
  8. Development and Benchmarking of Open Force Field 2.0.0: The Sage Small Molecule Force Field
    2023 111 citations Simon Boothroyd, Pavan Kumar Behara et al. Journal of Chemical Theory and Computation profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lee‐Ping Wang United States 34 4.2k 2.4k 2.1k 1.0k 1.0k 90 8.4k
Yingkai Zhang United States 48 3.9k 0.9× 2.8k 1.2× 2.9k 1.4× 622 0.6× 1.2k 1.2× 150 9.9k
Paolo Carloni Italy 54 6.1k 1.5× 1.6k 0.7× 1.4k 0.7× 1.0k 1.0× 722 0.7× 336 10.0k
Xiao He China 44 1.8k 0.4× 2.4k 1.0× 2.2k 1.0× 1.2k 1.2× 573 0.6× 271 7.3k
Francesco Luigi Gervasio United Kingdom 48 5.8k 1.4× 1.8k 0.8× 1.5k 0.7× 907 0.9× 1.2k 1.2× 138 8.6k
Adrian J. Mulholland United Kingdom 61 6.8k 1.6× 2.3k 1.0× 1.3k 0.6× 788 0.8× 1.3k 1.3× 275 11.5k
Edward Harder United States 30 4.7k 1.1× 1.5k 0.6× 1.8k 0.8× 784 0.8× 1.9k 1.9× 36 9.7k
Jing Huang China 32 7.2k 1.7× 1.8k 0.7× 1.4k 0.7× 979 1.0× 1.1k 1.1× 135 11.0k
Markus Meuwly Switzerland 43 2.4k 0.6× 2.4k 1.0× 3.4k 1.6× 1.8k 1.8× 974 1.0× 289 7.8k
Andriy Kovalenko Canada 44 2.9k 0.7× 1.9k 0.8× 2.8k 1.3× 738 0.7× 557 0.6× 185 7.0k
Andreas W. Götz United States 32 4.3k 1.0× 1.6k 0.7× 1.6k 0.7× 753 0.7× 779 0.8× 83 7.8k

Countries citing papers authored by Lee‐Ping Wang

Since Specialization
Citations

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

Fields of papers citing papers by Lee‐Ping Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lee‐Ping Wang. 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 Lee‐Ping Wang. The network helps show where Lee‐Ping Wang may publish in the future.

Co-authorship network of co-authors of Lee‐Ping Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Lee‐Ping Wang. A scholar is included among the top collaborators of Lee‐Ping Wang 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 Lee‐Ping Wang. Lee‐Ping Wang 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.
Behara, Pavan Kumar, Hyesu Jang, Joshua T. Horton, et al.. (2024). Benchmarking Quantum Mechanical Levels of Theory for Valence Parametrization in Force Fields. The Journal of Physical Chemistry B. 128(32). 7888–7902. 6 indexed citations
2.
Zhang, Ning, Damini Sood, Nanhao Chen, et al.. (2024). Temperature-dependent fold-switching mechanism of the circadian clock protein KaiB. Proceedings of the National Academy of Sciences. 121(51). e2412327121–e2412327121. 6 indexed citations
3.
Wang, Lee‐Ping, et al.. (2024). Reactant Discovery with an Ab Initio Nanoreactor: Exploration of Astrophysical N-Heterocycle Precursors and Formation Pathways. ACS Earth and Space Chemistry. 8(9). 1771–1783.
4.
Boothroyd, Simon, Pavan Kumar Behara, David F. Hahn, et al.. (2023). Development and Benchmarking of Open Force Field 2.0.0: The Sage Small Molecule Force Field. Journal of Chemical Theory and Computation. 19(11). 3251–3275. 111 indexed citations breakdown →
5.
Boothroyd, Simon, Lee‐Ping Wang, David L. Mobley, John D. Chodera, & Michael R. Shirts. (2022). Open Force Field Evaluator: An Automated, Efficient, and Scalable Framework for the Estimation of Physical Properties from Molecular Simulation. Journal of Chemical Theory and Computation. 18(6). 3566–3576. 28 indexed citations
6.
Ji, Yang, et al.. (2022). O-Acetyl Migration within the Sialic Acid Side Chain: A Mechanistic Study Using the Ab Initio Nanoreactor. Biochemistry. 61(18). 2007–2013. 8 indexed citations
7.
Varki, Ajit, et al.. (2022). SARS-CoV-2 and MERS-CoV Spike Protein Binding Studies Support Stable Mimic of Bound 9-O-Acetylated Sialic Acids. Molecules. 27(16). 5322–5322. 7 indexed citations
8.
Boothroyd, Simon, et al.. (2022). Improving Force Field Accuracy by Training against Condensed-Phase Mixture Properties. Journal of Chemical Theory and Computation. 18(6). 3577–3592. 14 indexed citations
9.
Ji, Yang, Aniruddha Sasmal, Wanqing Li, et al.. (2021). Reversible O-Acetyl Migration within the Sialic Acid Side Chain and Its Influence on Protein Recognition. ACS Chemical Biology. 16(10). 1951–1960. 22 indexed citations
10.
Smith, Daniel G. A., Simon Boothroyd, Hyesu Jang, et al.. (2021). Development and Benchmarking of Open Force Field v1.0.0—the Parsley Small-Molecule Force Field. Journal of Chemical Theory and Computation. 17(10). 6262–6280. 113 indexed citations
11.
Nerenberg, Paul S., et al.. (2021). Development and Validation of AMBER-FB15-Compatible Force Field Parameters for Phosphorylated Amino Acids. The Journal of Physical Chemistry B. 125(43). 11927–11942. 10 indexed citations
12.
Muddana, Hari S., et al.. (2020). Data-Driven Mapping of Gas-Phase Quantum Calculations to General Force Field Lennard-Jones Parameters. Journal of Chemical Theory and Computation. 16(2). 1115–1127. 15 indexed citations
13.
Seritan, Stefan, Christoph Bannwarth, B. Scott Fales, et al.. (2020). TeraChem: A graphical processing unit‐accelerated electronic structure package for large‐scale ab initio molecular dynamics. Wiley Interdisciplinary Reviews Computational Molecular Science. 11(2). 215 indexed citations breakdown →
14.
Slochower, David R., Niel M. Henriksen, Lee‐Ping Wang, et al.. (2019). Binding Thermodynamics of Host–Guest Systems with SMIRNOFF99Frosst 1.0.5 from the Open Force Field Initiative. Journal of Chemical Theory and Computation. 15(11). 6225–6242. 22 indexed citations
15.
Eastman, Peter, Jason Swails, John D. Chodera, et al.. (2017). OpenMM 7: Rapid development of high performance algorithms for molecular dynamics. PLoS Computational Biology. 13(7). e1005659–e1005659. 1736 indexed citations breakdown →
16.
Huang, Jing, Ye Mei, Gerhard König, et al.. (2017). An Estimation of Hybrid Quantum Mechanical Molecular Mechanical Polarization Energies for Small Molecules Using Polarizable Force-Field Approaches. Journal of Chemical Theory and Computation. 13(2). 679–695. 17 indexed citations
17.
Khedri, Zahra, An Xiao, Hai Yu, et al.. (2016). A Chemical Biology Solution to Problems with Studying Biologically Important but Unstable 9-O-Acetyl Sialic Acids. ACS Chemical Biology. 12(1). 214–224. 36 indexed citations
18.
Wang, Chi‐Yuen, et al.. (2016). Large earthquakes create vertical permeability by breaching aquitards. Water Resources Research. 52(8). 5923–5937. 80 indexed citations
19.
McGibbon, Robert T., Kyle A. Beauchamp, Matthew P. Harrigan, et al.. (2015). MDTraj: A Modern Open Library for the Analysis of Molecular Dynamics Trajectories. Biophysical Journal. 109(8). 1528–1532. 1537 indexed citations breakdown →
20.
Wang, Lee‐Ping, Teresa Head‐Gordon, Jay W. Ponder, et al.. (2014). Systematic Improvement on the Classical Molecular Model of Water. Biophysical Journal. 106(2). 403a–403a. 4 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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