Pan Tang

67 total papers · 1.5k total citations
51 papers, 1.1k citations indexed

About

Pan Tang is a scholar working on Molecular Biology, Pathology and Forensic Medicine and Surgery. According to data from OpenAlex, Pan Tang has authored 51 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 12 papers in Pathology and Forensic Medicine and 9 papers in Surgery. Recurrent topics in Pan Tang's work include Spine and Intervertebral Disc Pathology (10 papers), Spinal Hematomas and Complications (6 papers) and Protein Degradation and Inhibitors (5 papers). Pan Tang is often cited by papers focused on Spine and Intervertebral Disc Pathology (10 papers), Spinal Hematomas and Complications (6 papers) and Protein Degradation and Inhibitors (5 papers). Pan Tang collaborates with scholars based in China, United States and Azerbaijan. Pan Tang's co-authors include Liang Ouyang, Jifa Zhang, Shunwu Fan, Xuesheng Jiang, Jie Liu, Jiying Wang, Ziang Xie, Zhiwei Jie, Cheng-Ming Chiang and Zhijun Hu and has published in prestigious journals such as Chemical Communications, The FASEB Journal and Biochemical and Biophysical Research Communications.

In The Last Decade

Pan Tang

48 papers receiving 1.1k citations

Hit Papers

Unilateral biportal endos... 2022 2026 2023 2024 2022 25 50 75

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Pan Tang 595 267 163 160 131 51 1.1k
Masako Ogawa 590 1.0× 134 0.5× 187 1.1× 155 1.0× 283 2.2× 54 1.5k
Xiaoqing Zheng 579 1.0× 142 0.5× 99 0.6× 117 0.7× 201 1.5× 63 1.2k
Hitoshi Nakazato 644 1.1× 120 0.4× 84 0.5× 63 0.4× 112 0.9× 56 1.3k
Mary Johansen 408 0.7× 106 0.4× 223 1.4× 104 0.7× 179 1.4× 43 1.1k
Xiaowen Yu 437 0.7× 225 0.8× 129 0.8× 57 0.4× 71 0.5× 45 1.1k
Guido Orlandini 540 0.9× 288 1.1× 85 0.5× 52 0.3× 72 0.5× 49 1.4k
A Yoshida 435 0.7× 347 1.3× 49 0.3× 52 0.3× 100 0.8× 59 1.2k
Yuichi Nakamura 391 0.7× 123 0.5× 148 0.9× 43 0.3× 184 1.4× 62 1.0k
E. Bramm 326 0.5× 229 0.9× 219 1.3× 99 0.6× 39 0.3× 38 962
Ru Li 456 0.8× 57 0.2× 176 1.1× 118 0.7× 171 1.3× 67 1.4k

Countries citing papers authored by Pan Tang

Since Specialization
Citations

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

Fields of papers citing papers by Pan Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pan Tang

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

All Works

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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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