Lang Lin

26 papers receiving 662 citations

Peers

Lang Lin
Comparison fields: 5 of 66
  • Biochemistry 137
  • Cardiology and Cardiovascular Medicine 215
  • Physiology 198
  • Endocrinology, Diabetes and Metabolism 98
  • Transplantation 13
Replace Daniel Sollinger with:
Daniel Sollinger Germany
Sayaka Arakawa Japan
Christian Hengstenberg Germany
Yiling Fu United States
Vedat Tiyerili Germany
Elisabet Hilme Sweden
Seimi Satomi‐Kobayashi Japan
James Tomlinson United Kingdom
Petra Gratze Germany
Sumit Kar United States
Lang Lin relative to Daniel Sollinger Germany Daniel Sollinger's profile →
Citations per field
00.5×3.9×
Daniel Sollinger · 1×
Citations per year

Countries citing papers authored by Lang Lin

Since Specialization
Citations

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

Fields of papers citing papers by Lang Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199193
2 199482
3 199958
4 199152
5 201748
6 200239
7 201034
8 202034
9 199129
10 199428
11 199126
12 199221
13 200520
14 202118
15 202017
16 202216
17 202215
18 199114
19 202010
20 19909

About Lang Lin

Lang Lin is a scholar working on Physiology, Biochemistry, Molecular Biology, Pharmacology and Cardiology and Cardiovascular Medicine, having authored 28 papers that have together received 679 indexed citations. Recurring topics across this work include Nitric Oxide and Endothelin Effects (9 papers), Eicosanoids and Hypertension Pharmacology (6 papers), Inflammatory mediators and NSAID effects (4 papers), Renin-Angiotensin System Studies (3 papers), Helicobacter pylori-related gastroenterology studies (2 papers), Hedgehog Signaling Pathway Studies (2 papers), Tumors and Oncological Cases (2 papers) and Acute Lymphoblastic Leukemia research (2 papers). The work is most often cited by research in Biochemistry (137 citations), Cardiology and Cardiovascular Medicine (215 citations), Physiology (198 citations), Endocrinology, Diabetes and Metabolism (98 citations) and Transplantation (13 citations). Lang Lin has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Alberto Nasjletti, Michael Balazy, Charles T. Stier, Mahesh Mistry, William C. Sessa, Jianlin Huang, C. Noel Bairey Merz, Mark Doyle, Patrick J. Pagano and Daniel Edmundowicz. Their work appears in journals such as Hypertension, Circulation Research, Alimentary Pharmacology & Therapeutics, Journal of Cardiovascular Pharmacology and Neurological Research.

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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