Run‐Ling Wang

2.3k citations
79 papers · 1.3k · h-index 21

Impact in

Papers in

    • Protein Tyrosine Phosphatases 38
    • ATP Synthase and ATPases Research 10
    • Peroxisome Proliferator-Activated Receptors 7
    • Receptor Mechanisms and Signaling 6
    • Galectins and Cancer Biology 22

Run‐Ling Wang

78 papers receiving 1.3k citations

Peers

Run‐Ling Wang
Comparison fields: 5 of 96
  • Toxicology 91
  • Endocrinology, Diabetes and Metabolism 174
  • Molecular Biology 762
  • Organic Chemistry 305
  • Biochemistry 61
Replace Theodore Johnson with:
Theodore Johnson United States
Weiren Xu China
Jérémie Mortier Germany
Sangita B. Patel United States
Philipp Saiko Austria
Maria Giovanna Chini Italy
Gianluigi Lauro Italy
Yong-Seok Heo South Korea
Weitao Fu China
Run‐Ling Wang relative to Theodore Johnson United States Theodore Johnson's profile →
Citations per field
00.5×2.5×
Theodore Johnson · 1×
Citations per year

Countries citing papers authored by Run‐Ling Wang

Since Specialization
Citations

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

Fields of papers citing papers by Run‐Ling Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Run‐Ling Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Run‐Ling Wang Line = papers co-authored together Run‐Ling Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017108
2 201199
3 201299
4 201555
5 201748
6 201640
7 201637
8 201431
9 201830
10 201030
11 201627
12 201526
13 201124
14 201822
15 201421
16 201821
17 201721
18 201921
19 201520
20 201920

About Run‐Ling Wang

Run‐Ling Wang is a scholar working on Molecular Biology, Immunology, Organic Chemistry, Toxicology and Oncology, having authored 79 papers that have together received 1.3k indexed citations. Recurring topics across this work include Protein Tyrosine Phosphatases (38 papers), Galectins and Cancer Biology (22 papers), Bioactive Compounds and Antitumor Agents (15 papers), ATP Synthase and ATPases Research (10 papers), Synthesis and biological activity (9 papers), Peroxisome Proliferator-Activated Receptors (7 papers), Receptor Mechanisms and Signaling (6 papers) and Computational Drug Discovery Methods (6 papers). The work is most often cited by research in Toxicology (91 citations), Endocrinology, Diabetes and Metabolism (174 citations), Molecular Biology (762 citations), Organic Chemistry (305 citations) and Biochemistry (61 citations). Run‐Ling Wang has collaborated with scholars based in China, New Zealand and United States. Frequent co-authors include Ying Ma, Weiren Xu, Shuqing Wang, Kuo‐Chen Chou, Xian‐Chao Cheng, Peng Yu, Hua Sun, Weiya Li, Wei‐Li Dong and Xiaobo Li. Their work appears in journals such as Journal of Biomolecular Structure and Dynamics, Oncotarget, Bioorganic & Medicinal Chemistry Letters, European Journal of Medicinal Chemistry and Bioorganic Chemistry.

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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