Wan Wang

626 citations
31 papers · 436 · h-index 12

Impact in

Papers in

    • Circular RNAs in diseases 3
    • RNA modifications and cancer 3
    • Breast Cancer Treatment Studies 2
    • Cancer-related molecular mechanisms research 2
    • Cancer, Hypoxia, and Metabolism 2

Wan Wang

30 papers receiving 435 citations

Peers

Wan Wang
Comparison fields: 5 of 96
  • Hepatology 40
  • Cancer Research 57
  • Genetics 35
  • Neurology 42
  • Epidemiology 89
Replace Martin Hsiu‐Chu Lin with:
Martin Hsiu‐Chu Lin Taiwan
Korinna Pilz Germany
Hun Soo Kim South Korea
Matteo Vecellio United Kingdom
Mahtab Bahramsoltani Germany
Francisco Lopez Spain
Fei Kuang China
Yefei Wang China
Cynthia A. Ballenger United States
Wan Wang relative to Martin Hsiu‐Chu Lin Taiwan Martin Hsiu‐Chu Lin's profile →
Citations per field
00.5×1.5×2.5×
Martin Hsiu‐Chu Lin · 1×
Citations per year

Countries citing papers authored by Wan Wang

Since Specialization
Citations

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

Fields of papers citing papers by Wan Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201452
2 201643
3 201442
4 201941
5 201539
6 202035
7 201829
8 202124
9 201817
10 201615
11 198714
12 201613
13 202210
14 20098
15 20218
16
Alkaloids from root tubers of Stephania kwangsiensis H.S.Lo and their effects on proliferation and apoptosis of lung NCI-H446 cells.
20167
17 20247
18 20215
19
Differential effects of estrogen and estrogen receptor antagonist, ICI 182 780, on the expression of calbindin-D9k in rat pituitary prolactinoma GH₃ cells.
20144
20 20233

About Wan Wang

Wan Wang is a scholar working on Molecular Biology, Cancer Research, Epidemiology, Oncology and Surgery, having authored 31 papers that have together received 436 indexed citations. Recurring topics across this work include Circular RNAs in diseases (3 papers), RNA modifications and cancer (3 papers), Amyotrophic Lateral Sclerosis Research (2 papers), Autophagy in Disease and Therapy (2 papers), Breast Cancer Treatment Studies (2 papers), Cancer-related molecular mechanisms research (2 papers), Neurogenetic and Muscular Disorders Research (2 papers) and Cancer, Hypoxia, and Metabolism (2 papers). The work is most often cited by research in Hepatology (40 citations), Cancer Research (57 citations), Genetics (35 citations), Neurology (42 citations) and Epidemiology (89 citations). Wan Wang has collaborated with scholars based in China, United States and Austria. Frequent co-authors include Pu Shi, Honggang Cui, J. Andrew MacKay, Fei Guo, Jingyi Yang, Huiying Liu, Yi-An Lin, Weisong Duan, Di Wen and Zhongyao Li. Their work appears in journals such as Journal of Cancer, Cell Death Discovery, Genes and Environment, The Science of The Total Environment and The Journal of Maternal-Fetal & Neonatal Medicine.

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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