Hang Wang

3.7k citations
164 papers · 2.7k · 1 hit paper · h-index 28

Impact in

    • Cancer, Hypoxia, and Metabolism
    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation

Papers in

Hang Wang

147 papers receiving 2.7k citations

Hang Wang's Hit Papers

Metabolomic machine learning predictor for diagnosis and prognosis of gastric cancer 2024 · 98 citations
980+1Years since publication255075

Peers

Hang Wang
Comparison fields: 5 of 157
  • Cancer Research 387
  • Orthodontics 91
  • Hepatology 158
  • Oncology 461
  • Oral Surgery 105
Replace Mariko Tanaka with:
Mariko Tanaka Japan
André Luiz Sena Guimarães Brazil
Sung‐Chul Lim South Korea
Jung‐Hyun Park South Korea
Lu He China
Cristiana Tănase Romania
Elżbieta Kaczmarek Poland
Tadashi Nakanishi Japan
Maria Greabu Romania
Mark N. Gillespie United States
Hang Wang relative to Mariko Tanaka Japan Mariko Tanaka's profile →
Citations per field
00.5×3.5×
Mariko Tanaka · 1×
Citations per year

Countries citing papers authored by Hang Wang

Since Specialization
Citations

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

Fields of papers citing papers by Hang Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 164 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013132
2 2022118
3 2011114
4
Metabolomic machine learning predictor for diagnosis and prognosis of gastric cancer
Hit paper breakdown →
202498
5 201588
6 202282
7 202076
8 202270
9 201167
10 201566
11 201865
12 201962
13 201957
14 201754
15 201847
16 200746
17 201644
18 201543
19 202141
20 201637

About Hang Wang

Hang Wang is a scholar working on Molecular Biology, Oncology, Pulmonary and Respiratory Medicine, Cancer Research and Epidemiology, having authored 164 papers that have together received 2.7k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (9 papers), Retinal Imaging and Analysis (9 papers), Cancer Immunotherapy and Biomarkers (8 papers), Glaucoma and retinal disorders (8 papers), Retinal and Optic Conditions (8 papers), Cerebral Venous Sinus Thrombosis (7 papers), Bone Metabolism and Diseases (7 papers) and Cancer, Hypoxia, and Metabolism (7 papers). The work is most often cited by research in Cancer Research (387 citations), Orthodontics (91 citations), Hepatology (158 citations), Oncology (461 citations) and Oral Surgery (105 citations). Hang Wang has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Hua Qu, Huacong Deng, Chang‐Jer Wu, Jiefei Shen, Huili Wei, Xuelei Ma, Zhipeng Li, Yamei Chen, Quanyi Lu and Yi-Lin Chan. Their work appears in journals such as Cell Biology International, Frontiers in Oncology, PLoS ONE, Archives of Oral Biology and RSC Advances.

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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