Jun Fan

2.0k citations
99 papers · 1.3k indexed · h-index 20

Impact in

Papers in

Jun Fan

92 papers receiving 1.3k citations

Peers

Jun Fan
Comparison fields: 5 of 111
  • Endocrinology, Diabetes and Metabolism 588
  • Genetics 273
  • Cancer Research 184
  • Epidemiology 252
  • Cellular and Molecular Neuroscience 118
Replace Anne‐Marie Madec with:
Anne‐Marie Madec France
Song-Guang Ren United States
Hindi Al‐Hindi Saudi Arabia
Sigrid Hoffmann Germany
Motohiro Nomura Japan
Shohei Kohno Japan
Yu Sun China
Monika Buraczyńska Poland
Xingyao Bu China
Jun Fan relative to Anne‐Marie Madec France Anne‐Marie Madec's profile →
Citations per field
00.5×2.8×
Anne‐Marie Madec · 1×
Citations per year

Countries citing papers authored by Jun Fan

Since Specialization
Citations

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

Fields of papers citing papers by Jun Fan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20240
2 20242
3 20237
4 20233
5 20233
6 202325
7 20238
8 202318
9 20221
10 202214
11 202211
12 202110
13 202110
14 20213
15 202111
16 20204
17 20192
18 201914
19
Variation patterns of main taxonomic characters of Berberis sublevis (Berberidaceae) from Yunnan Province.
20151
20
Cloning and Sequence Analysis of Chinese Cabbage Chitinase Gene CHB4
20071

About Jun Fan

Jun Fan is a scholar working on Endocrinology, Diabetes and Metabolism, Genetics, Cancer Research, Surgery and Pulmonary and Respiratory Medicine, having authored 99 papers that have together received 1.3k indexed citations. Recurring topics across this work include Pituitary Gland Disorders and Treatments (26 papers), Glioma Diagnosis and Treatment (17 papers), Growth Hormone and Insulin-like Growth Factors (11 papers), Head and Neck Surgical Oncology (10 papers), RNA modifications and cancer (10 papers), Cancer, Hypoxia, and Metabolism (7 papers), Epigenetics and DNA Methylation (7 papers) and Meningioma and schwannoma management (7 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (588 citations), Genetics (273 citations), Cancer Research (184 citations), Epidemiology (252 citations) and Cellular and Molecular Neuroscience (118 citations). Jun Fan has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Songtao Qi, Charles H. Lang, Jun Pan, Junxiang Peng, Marcin Wojnar, Yuntao Lu, Michael C. Theodorakis, Xian Zhang, Binghui Qiu and Abdullah Bereket. Their work appears in journals such as Environmental Pollution, Journal of neurosurgery, Acta Neurochirurgica, Frontiers in Oncology and International Journal of Radiation Oncology*Biology*Physics.

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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