Lane Votapka

1.1k total citations
25 papers, 784 citations indexed

About

Lane Votapka is a scholar working on Molecular Biology, Computational Theory and Mathematics and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Lane Votapka has authored 25 papers receiving a total of 784 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 7 papers in Computational Theory and Mathematics and 4 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Lane Votapka's work include Protein Structure and Dynamics (16 papers), Computational Drug Discovery Methods (7 papers) and Gene Regulatory Network Analysis (5 papers). Lane Votapka is often cited by papers focused on Protein Structure and Dynamics (16 papers), Computational Drug Discovery Methods (7 papers) and Gene Regulatory Network Analysis (5 papers). Lane Votapka collaborates with scholars based in United States, Germany and Japan. Lane Votapka's co-authors include Rommie E. Amaro, Jacob D. Durrant, Jesper Givskov Sørensen, R. Mitchell Bush, Robert V. Swift, Ross C. Walker, Wilfred W. Li, Anupam Anand Ojha, Christopher T. Lee and Rebecca C. Wade and has published in prestigious journals such as Nature Communications, Bioinformatics and The Journal of Physical Chemistry B.

In The Last Decade

Lane Votapka

25 papers receiving 778 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lane Votapka United States 13 614 179 128 84 73 25 784
Gregory M. Lee United States 14 728 1.2× 66 0.4× 69 0.5× 156 1.9× 49 0.7× 21 948
Kerry M. Swift United States 13 871 1.4× 79 0.4× 85 0.7× 93 1.1× 46 0.6× 31 1.1k
Marharyta Petukh United States 17 1.2k 2.0× 161 0.9× 40 0.3× 215 2.6× 105 1.4× 26 1.6k
Guido Scarabelli United States 13 632 1.0× 111 0.6× 43 0.3× 96 1.1× 15 0.2× 17 820
Sankar Basu India 15 614 1.0× 147 0.8× 30 0.2× 194 2.3× 39 0.5× 39 791
Lidio Meireles United States 6 898 1.5× 204 1.1× 32 0.3× 202 2.4× 41 0.6× 6 1.1k
Anthony Ivetac United States 18 1.5k 2.4× 218 1.2× 30 0.2× 112 1.3× 81 1.1× 24 1.9k
Dora Toledo Warshaviak United States 16 755 1.2× 178 1.0× 24 0.2× 61 0.7× 66 0.9× 20 1.1k
Disha Patel United States 14 348 0.6× 97 0.5× 176 1.4× 73 0.9× 45 0.6× 31 609
Chiduru Watanabe Japan 18 550 0.9× 270 1.5× 28 0.2× 157 1.9× 151 2.1× 55 898

Countries citing papers authored by Lane Votapka

Since Specialization
Citations

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

Fields of papers citing papers by Lane Votapka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lane Votapka

This figure shows the co-authorship network connecting the top 25 collaborators of Lane Votapka. A scholar is included among the top collaborators of Lane Votapka 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 Lane Votapka. Lane Votapka 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.
Votapka, Lane, et al.. (2024). Prediction of Threonine-Tyrosine Kinase Receptor–Ligand Unbinding Kinetics with Multiscale Milestoning and Metadynamics. The Journal of Physical Chemistry Letters. 15(42). 10473–10478. 4 indexed citations
2.
Ojha, Anupam Anand, Lane Votapka, & Rommie E. Amaro. (2024). Advances and Challenges in Milestoning Simulations for Drug–Target Kinetics. Journal of Chemical Theory and Computation. 20(22). 9759–9769. 4 indexed citations
3.
Ojha, Anupam Anand, Lane Votapka, Gary Huber, Shang Gao, & Rommie E. Amaro. (2024). An Introductory Tutorial to the SEEKR2 (Simulation Enabled Estimation of Kinetic Rates v. 2) Multiscale Milestoning Software [Article v1.0]. 5(1). 2359–2359. 1 indexed citations
4.
Votapka, Lane, et al.. (2024). NetSci: A Library for High Performance Biomolecular Simulation Network Analysis Computation. Journal of Chemical Information and Modeling. 64(20). 7966–7976. 2 indexed citations
5.
Ojha, Anupam Anand, Lane Votapka, & Rommie E. Amaro. (2023). QMrebind: incorporating quantum mechanical force field reparameterization at the ligand binding site for improved drug-target kinetics through milestoning simulations. Chemical Science. 14(45). 13159–13175. 6 indexed citations
6.
Kim, Sang Hoon, Fiona L. Kearns, Mia A. Rosenfeld, et al.. (2023). SARS-CoV-2 evolved variants optimize binding to cellular glycocalyx. Cell Reports Physical Science. 4(4). 101346–101346. 26 indexed citations
7.
Hung, N., Lane Votapka, Keya Joshi, et al.. (2022). Gaussian Accelerated Molecular Dynamics in OpenMM. The Journal of Physical Chemistry B. 126(31). 5810–5820. 11 indexed citations
8.
Votapka, Lane, et al.. (2022). Brownian dynamics simulations of biomolecular diffusional association processes. Wiley Interdisciplinary Reviews Computational Molecular Science. 13(3). 12 indexed citations
9.
Votapka, Lane, et al.. (2022). SEEKR2: Versatile Multiscale Milestoning Utilizing the OpenMM Molecular Dynamics Engine. Journal of Chemical Information and Modeling. 62(13). 3253–3262. 24 indexed citations
10.
Votapka, Lane, et al.. (2022). Brownian dynamics simulations of biomolecular diffusional association processes. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations
11.
12.
Votapka, Lane, et al.. (2017). SEEKR: Simulation Enabled Estimation of Kinetic Rates, A Computational Tool to Estimate Molecular Kinetics and Its Application to Trypsin–Benzamidine Binding. The Journal of Physical Chemistry B. 121(15). 3597–3606. 71 indexed citations
13.
Votapka, Lane. (2016). Numerical and Computational Solutions for Biochemical Kinetics, Druggability, and Simulation. eScholarship (California Digital Library). 1 indexed citations
14.
Votapka, Lane, Christopher T. Lee, & Rommie E. Amaro. (2016). Two Relations to Estimate Membrane Permeability Using Milestoning. The Journal of Physical Chemistry B. 120(33). 8606–8616. 37 indexed citations
15.
Boras, Britton, et al.. (2015). Bridging scales through multiscale modeling: a case study on protein kinase A. Frontiers in Physiology. 6. 250–250. 19 indexed citations
16.
Votapka, Lane & Rommie E. Amaro. (2015). Multiscale Estimation of Binding Kinetics Using Brownian Dynamics, Molecular Dynamics and Milestoning. PLoS Computational Biology. 11(10). e1004381–e1004381. 59 indexed citations
17.
Durrant, Jacob D., Lane Votapka, Jesper Givskov Sørensen, & Rommie E. Amaro. (2014). POVME 2.0: An Enhanced Tool for Determining Pocket Shape and Volume Characteristics. Journal of Chemical Theory and Computation. 10(11). 5047–5056. 187 indexed citations
18.
Durrant, Jacob D., et al.. (2014). Weighted Implementation of Suboptimal Paths (WISP): An Optimized Algorithm and Tool for Dynamical Network Analysis. Journal of Chemical Theory and Computation. 10(2). 511–517. 143 indexed citations
19.
Votapka, Lane & Rommie E. Amaro. (2012). Multistructural hot spot characterization with FTProd. Bioinformatics. 29(3). 393–394. 12 indexed citations
20.
Amaro, Rommie E., Robert V. Swift, Lane Votapka, et al.. (2011). Mechanism of 150-cavity formation in influenza neuraminidase. Nature Communications. 2(1). 388–388. 117 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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