Ping Wan

1.5k citations
53 papers · 1.1k · h-index 21

Impact in

  • Physiology top 10%
    • Adenosine and Purinergic Signaling
    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research

Papers in

    • Developmental Biology and Gene Regulation 3
    • RNA Research and Splicing 3
    • Muscle Physiology and Disorders 3
    • Machine Learning in Bioinformatics 3
    • Genomics and Phylogenetic Studies 3
    • Metabolomics and Mass Spectrometry Studies 2
    • Cellular Mechanics and Interactions 5
    • Cellular transport and secretion 2

Ping Wan

46 papers receiving 1.0k citations

Peers

Ping Wan
Comparison fields: 5 of 114
  • Physiology 49
  • Cancer Research 126
  • Cell Biology 121
  • Molecular Biology 481
  • Pharmacology 47
Replace Torben Særmark with:
Torben Særmark Denmark
Cornelia H. de Moor United Kingdom
Ralph SCHALOSKE Germany
Mariana S. Araújo Brazil
Xiaoling Jiang China
Joseph Orly Israel
Jianying Shen China
Kuniaki Mukai Japan
Genevieve Stapleton United Kingdom
Marina Wolfson Israel
Ping Wan relative to Torben Særmark Denmark Torben Særmark's profile →
Citations per field
00.5×5.5×
Torben Særmark · 1×
Citations per year

Countries citing papers authored by Ping Wan

Since Specialization
Citations

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

Fields of papers citing papers by Ping Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ping Wan, 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 Ping Wan Line = papers co-authored together Ping Wan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017121
2 2007116
3 201671
4 201664
5 200657
6 201150
7 200544
8 201235
9 201934
10 201634
11 201233
12 201233
13 201932
14 201432
15 201527
16 201827
17 201326
18 201126
19 201924
20 201323

About Ping Wan

Ping Wan is a scholar working on Molecular Biology, Cell Biology, Surgery, Immunology and Oncology, having authored 53 papers that have together received 1.1k indexed citations. Recurring topics across this work include Cellular Mechanics and Interactions (5 papers), Developmental Biology and Gene Regulation (3 papers), RNA Research and Splicing (3 papers), Muscle Physiology and Disorders (3 papers), Machine Learning in Bioinformatics (3 papers), Genomics and Phylogenetic Studies (3 papers), Cellular transport and secretion (2 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). The work is most often cited by research in Physiology (49 citations), Cancer Research (126 citations), Cell Biology (121 citations), Molecular Biology (481 citations) and Pharmacology (47 citations). Ping Wan has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Jiong Chen, Jun Luo, Aiping Bai, Yuan Guo, Yuping Ren, Jingshu Wang, Gong Yang, Jing Wu, Lili Lu and Yougen Wu. Their work appears in journals such as Frontiers in Psychiatry, Development, Scientific Reports, PLoS ONE and Neuroscience Bulletin.

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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