Yan Pan

1.3k total citations
53 papers, 1.1k citations indexed

About

Yan Pan is a scholar working on Electrical and Electronic Engineering, Control and Systems Engineering and Spectroscopy. According to data from OpenAlex, Yan Pan has authored 53 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Electrical and Electronic Engineering, 12 papers in Control and Systems Engineering and 11 papers in Spectroscopy. Recurrent topics in Yan Pan's work include Mass Spectrometry Techniques and Applications (11 papers), HVDC Systems and Fault Protection (10 papers) and Photoreceptor and optogenetics research (8 papers). Yan Pan is often cited by papers focused on Mass Spectrometry Techniques and Applications (11 papers), HVDC Systems and Fault Protection (10 papers) and Photoreceptor and optogenetics research (8 papers). Yan Pan collaborates with scholars based in United States, Canada and China. Yan Pan's co-authors include Lars Konermann, Xin Tong, Leonid S. Brown, Bradley B. Stocks, William J. Meath, Fabing Duan, T. Baldwin, H. Kreek, François Chapeau‐Blondeau and Derek Abbott and has published in prestigious journals such as Journal of the American Chemical Society, SHILAP Revista de lepidopterología and Journal of Molecular Biology.

In The Last Decade

Yan Pan

50 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yan Pan United States 21 383 377 283 157 139 53 1.1k
Thomas Schulte Germany 20 379 1.0× 49 0.1× 255 0.9× 210 1.3× 478 3.4× 69 1.6k
Jürgen Zanghellini Austria 28 1.1k 3.0× 221 0.6× 88 0.3× 88 0.6× 612 4.4× 82 2.3k
Ramachandran Gnanasekaran United States 13 159 0.4× 90 0.2× 89 0.3× 27 0.2× 235 1.7× 40 636
Irwin Tobias United States 22 543 1.4× 113 0.3× 74 0.3× 88 0.6× 289 2.1× 44 1.1k
K. Yamafuji Japan 27 122 0.3× 66 0.2× 324 1.1× 239 1.5× 334 2.4× 148 2.4k
Martin Graham United Kingdom 12 195 0.5× 81 0.2× 560 2.0× 40 0.3× 30 0.2× 36 1.2k
David Andrews United States 21 263 0.7× 101 0.3× 169 0.6× 24 0.2× 273 2.0× 100 1.5k
Guang Song United States 23 1.2k 3.0× 181 0.5× 27 0.1× 185 1.2× 201 1.4× 71 1.7k
Christoph Wehmeyer Germany 12 1.3k 3.5× 219 0.6× 69 0.2× 15 0.1× 203 1.5× 15 1.9k
Hyungsik Lim United States 25 800 2.1× 21 0.1× 535 1.9× 399 2.5× 543 3.9× 70 2.1k

Countries citing papers authored by Yan Pan

Since Specialization
Citations

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

Fields of papers citing papers by Yan Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yan Pan

This figure shows the co-authorship network connecting the top 25 collaborators of Yan Pan. A scholar is included among the top collaborators of Yan Pan 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 Yan Pan. Yan Pan 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.
Pan, Yan, et al.. (2025). Automated seed counting using image processing and deep learning. Frontiers in Plant Science. 16. 1659781–1659781.
2.
Pan, Yan, et al.. (2024). DOA Estimation on One-Bit Quantization Observations through Noise-Boosted Multiple Signal Classification. Sensors. 24(14). 4719–4719. 3 indexed citations
3.
Pan, Yan, et al.. (2023). Optimal Noise-Boosted Estimator Design Via Adaptive Stochastic Resonance. Fluctuation and Noise Letters. 22(3). 1 indexed citations
4.
Pan, Yan, Fabing Duan, François Chapeau‐Blondeau, & Derek Abbott. (2018). Noise Enhancement in Robust Estimation of Location. IEEE Transactions on Signal Processing. 66(8). 1953–1966. 21 indexed citations
5.
Pan, Yan, et al.. (2017). Exploiting vibrational resonance in weak-signal detection. Physical review. E. 96(2). 22141–22141. 31 indexed citations
6.
Dong, Dong, Luis Garces, Mohammed Agamy, et al.. (2016). Control and operation of medium-voltage high-power bi-directional resonant DC-DC converters in shipboard dc distribution systems. 1–9. 8 indexed citations
7.
Pan, Yan, Hadeesha Piyadasa, Joe D. O’Neil, & Lars Konermann. (2012). Conformational Dynamics of a Membrane Transport Protein Probed by H/D Exchange and Covalent Labeling: The Glycerol Facilitator. Journal of Molecular Biology. 416(3). 400–413. 44 indexed citations
8.
Konermann, Lars & Yan Pan. (2012). Exploring membrane protein structural features by oxidative labeling and mass spectrometry. Expert Review of Proteomics. 9(5). 497–504. 19 indexed citations
9.
Pan, Yan, Xiang Ruan, Miguel A. Valvano, & Lars Konermann. (2012). Validation of Membrane Protein Topology Models by Oxidative Labeling and Mass Spectrometry. Journal of the American Society for Mass Spectrometry. 23(5). 889–898. 30 indexed citations
10.
Pan, Yan, Leonid S. Brown, & Lars Konermann. (2011). Kinetic Folding Mechanism of an Integral Membrane Protein Examined by Pulsed Oxidative Labeling and Mass Spectrometry. Journal of Molecular Biology. 410(1). 146–158. 34 indexed citations
11.
Konermann, Lars, Yan Pan, & Bradley B. Stocks. (2011). Protein folding mechanisms studied by pulsed oxidative labeling and mass spectrometry. Current Opinion in Structural Biology. 21(5). 634–640. 20 indexed citations
12.
13.
Pan, Yan & Lars Konermann. (2010). Membrane protein structural insights from chemical labeling and mass spectrometry. The Analyst. 135(6). 1191–1191. 32 indexed citations
14.
Pan, Yan, Leonid S. Brown, & Lars Konermann. (2010). Hydrogen/deuterium exchange mass spectrometry and optical spectroscopy as complementary tools for studying the structure and dynamics of a membrane protein. International Journal of Mass Spectrometry. 302(1-3). 3–11. 20 indexed citations
15.
Konermann, Lars, Bradley B. Stocks, Yan Pan, & Xin Tong. (2009). Mass spectrometry combined with oxidative labeling for exploring protein structure and folding. Mass Spectrometry Reviews. 29(4). 651–667. 62 indexed citations
16.
Pan, Yan, Leonid S. Brown, & Lars Konermann. (2009). Mapping the Structure of an Integral Membrane Protein under Semi-Denaturing Conditions by Laser-Induced Oxidative Labeling and Mass Spectrometry. Journal of Molecular Biology. 394(5). 968–981. 41 indexed citations
17.
Pan, Yan. (2009). Noise Pattern Analysis Based Ground Fault Location Approach for Ungrounded Electrical Distribution Systems. 4 indexed citations
18.
Konermann, Lars, Xin Tong, & Yan Pan. (2008). Protein structure and dynamics studied by mass spectrometry: H/D exchange, hydroxyl radical labeling, and related approaches. Journal of Mass Spectrometry. 43(8). 1021–1036. 149 indexed citations
19.
Pan, Yan, G.B. Jansen, T.F. Duffield, et al.. (2004). Genetic Susceptibility to Neospora caninum Infection in Holstein Cattle in Ontario. Journal of Dairy Science. 87(11). 3967–3975. 38 indexed citations
20.
Pan, Yan, P. Boettcher, & John P. Gibson. (2001). Bayesian Segregation Analysis of Somatic Cell Scores of Ontario Holstein Cattle. Journal of Dairy Science. 84(12). 2796–2802. 6 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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