Jun Lin

1.7k citations
65 papers · 1.3k · h-index 23

Impact in

Papers in

Jun Lin

65 papers receiving 1.3k citations

Peers

Jun Lin
Comparison fields: 5 of 79
  • Reproductive Medicine 735
  • Obstetrics and Gynecology 528
  • Immunology 353
  • Cancer Research 113
  • Public Health, Environmental and Occupational Health 157
Replace Fuminori Taniguchi with:
Fuminori Taniguchi Japan
Krzysztof Szyłło Poland
Zainab Basir United States
Camran Nezhat United States
Hua Duan China
Andrew K. Edwards Canada
Julie M. Hastings United States
I. Ryan United States
Andrzej Malinowski Poland
Brianna Cloke United Kingdom
Jun Lin relative to Fuminori Taniguchi Japan Fuminori Taniguchi's profile →
Citations per field
00.5×1.5×2.4×
Fuminori Taniguchi · 1×
Citations per year

Countries citing papers authored by Jun Lin

Since Specialization
Citations

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

Fields of papers citing papers by Jun Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200985
2 200980
3 200873
4 202172
5 200565
6 201058
7 200657
8
Gonadotropin-releasing hormone agonists and laparoscopy in the treatment of adenomyosis with infertility.
200050
9 202144
10 200940
11 201632
12 200831
13 200428
14 201828
15
Glutathione S-transferase M1 and T1 genotypes and endometriosis risk: a case-controlled study.
200327
16 202026
17 200725
18 201925
19 202024
20 201824

About Jun Lin

Jun Lin is a scholar working on Reproductive Medicine, Obstetrics and Gynecology, Molecular Biology, Immunology and Pulmonary and Respiratory Medicine, having authored 65 papers that have together received 1.3k indexed citations. Recurring topics across this work include Endometriosis Research and Treatment (35 papers), Reproductive System and Pregnancy (9 papers), Uterine Myomas and Treatments (9 papers), Endometrial and Cervical Cancer Treatments (7 papers), Gynecological conditions and treatments (5 papers), Estrogen and related hormone effects (3 papers), Protein Tyrosine Phosphatases (3 papers) and Cancer-related molecular mechanisms research (3 papers). The work is most often cited by research in Reproductive Medicine (735 citations), Obstetrics and Gynecology (528 citations), Immunology (353 citations), Cancer Research (113 citations) and Public Health, Environmental and Occupational Health (157 citations). Jun Lin has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Xinmei Zhang, Kaihong Xu, Junyan Ma, Hong Xu, Caiyun Zhou, Lin Deng, Ruijin Wu, Xiufeng Huang, Hong Zhan and Yuli Qian. Their work appears in journals such as Fertility and Sterility, Reproductive Sciences, International Journal of Gynecology & Obstetrics, Acta Histochemica and Archives of Gynecology and Obstetrics.

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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