Yan Ling

1.8k citations
80 papers · 1.3k · 1 hit paper · h-index 21

Impact in

Papers in

Yan Ling

77 papers receiving 1.3k citations

Yan Ling's Hit Papers

Hepatocyte-derived extracellular vesicles promote endothelial inflammation and atherogenesis via microRNA-1 2019 · 225 citations
2250+2+4Years since publication50100150200

Peers

Yan Ling
Comparison fields: 5 of 98
  • Endocrinology, Diabetes and Metabolism 241
  • Cancer Research 212
  • Immunology and Allergy 59
  • Immunology 143
  • Molecular Biology 452
Replace Aiko Inoue with:
Aiko Inoue Japan
Shufang Wu China
Akio Kawakami Japan
Sunil K. Halder United States
Kathleen Gabrielson United States
Jinchuan Yan China
I. Sophie T. Bos Netherlands
Nihan Erginel‐Ünaltuna Türkiye
Jingang Zheng China
Emilie Distel France
Yan Ling relative to Aiko Inoue Japan Aiko Inoue's profile →
Citations per field
00.5×1.5×1.8×
Aiko Inoue · 1×
Citations per year

Countries citing papers authored by Yan Ling

Since Specialization
Citations

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

Fields of papers citing papers by Yan Ling

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 80 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Hepatocyte-derived extracellular vesicles promote endothelial inflammation and atherogenesis via microRNA-1
Hit paper breakdown →
2019225
2 200356
3 200756
4 201351
5 200644
6 201242
7 201239
8 202136
9 202034
10 201633
11 201933
12 200529
13 201828
14 201827
15 201127
16 201225
17 201124
18 201724
19 201122
20 201621

About Yan Ling

Yan Ling is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology, Oncology, Pulmonary and Respiratory Medicine and Surgery, having authored 80 papers that have together received 1.3k indexed citations. Recurring topics across this work include Lung Cancer Treatments and Mutations (7 papers), Thyroid Disorders and Treatments (6 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers), Thyroid Cancer Diagnosis and Treatment (5 papers), Lung Cancer Research Studies (4 papers), Vitamin D Research Studies (4 papers), Lipoproteins and Cardiovascular Health (4 papers) and Reproductive System and Pregnancy (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (241 citations), Cancer Research (212 citations), Immunology and Allergy (59 citations), Immunology (143 citations) and Molecular Biology (452 citations). Yan Ling has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Xin Gao, David R. Clemmons, Pu Xia, Yan Yan, Qi Chen, Wei Wang, Fangjie Jiang, Xiaomu Li, Laura A. Maile and Tianyu Zhai. Their work appears in journals such as The Oncologist, Brain Research, Frontiers in Endocrinology, Molecular Endocrinology and Cardiovascular Diabetology.

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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