Jun Wang

258 papers receiving 6.6k citations

Jun Wang's Hit Papers

Meta-analysis of modifiable risk factors for Alzheimer's disease 2015 · 445 citations
4450+3+7Years since publication100200300400

Peers

Jun Wang
Comparison fields: 5 of 166
  • Cancer Research 934
  • Pathology and Forensic Medicine 760
  • Geriatrics and Gerontology 137
  • Oncology 983
  • Pharmacology 543
Replace Javier Dı́ez with:
Javier Dı́ez Spain
Fabrizio Montecucco Italy
Keith M. Channon United Kingdom
Atsushi Takahashi Japan
Georg Ertl Germany
Rosario Scalia United States
Tohru Minamino Japan
Leong L. Ng United Kingdom
Johann Bauersachs Germany
Koichi Node Japan
Jun Wang relative to Javier Dı́ez Spain Javier Dı́ez's profile →
Citations per field
00.5×1.7×
Javier Dı́ez · 1×
Citations per year

Countries citing papers authored by Jun Wang

Since Specialization
Citations

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

Fields of papers citing papers by Jun Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 278 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Meta-analysis of modifiable risk factors for Alzheimer's disease
Hit paper breakdown →
2015445
2 2013250
3 1998200
4 2002148
5 2008144
6 2012141
7 2007132
8 2004130
9 2014114
10
Metabolic consequences of a reversed pH gradient in rat tumors.
1994111
11 2003107
12 2016106
13
Defects of DNA mismatch repair in human prostate cancer.
2001105
14
Placenta inflammation is closely associated with gestational diabetes mellitus.
2021102
15 2011100
16 200394
17 201892
18 200690
19 199989
20 201585

About Jun Wang

Jun Wang is a scholar working on Molecular Biology, Oncology, Cancer Research, Pathology and Forensic Medicine and Pulmonary and Respiratory Medicine, having authored 278 papers that have together received 6.8k indexed citations. Recurring topics across this work include Cancer, Lipids, and Metabolism (17 papers), Estrogen and related hormone effects (14 papers), Epigenetics and DNA Methylation (13 papers), Cannabis and Cannabinoid Research (12 papers), Breast Cancer Treatment Studies (11 papers), Pregnancy and preeclampsia studies (10 papers), Protease and Inhibitor Mechanisms (8 papers) and Blood Coagulation and Thrombosis Mechanisms (8 papers). The work is most often cited by research in Cancer Research (934 citations), Pathology and Forensic Medicine (760 citations), Geriatrics and Gerontology (137 citations), Oncology (983 citations) and Pharmacology (543 citations). Jun Wang has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Natsuo Ueda, Hau C. Kwaan, Coral A. Lamartiniere, Lin Tan, Jieqiong Li, Jin‐Tai Yu, Lan Tan, Teng Jiang, Meng‐Shan Tan and Hui-Fu Wang. Their work appears in journals such as Frontiers in Oncology, Breast Cancer Research and Treatment, Cancer Prevention Research, Journal of Cancer and Hormones and Cancer.

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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