H. Jin

26 papers receiving 904 citations

Peers

H. Jin
Comparison fields: 5 of 73
  • Endocrine and Autonomic Systems 148
  • Cardiology and Cardiovascular Medicine 391
  • Behavioral Neuroscience 53
  • Physiology 302
  • Biochemistry 75
Replace Peter Rohmeiss with:
Peter Rohmeiss Germany
Conrado Johns United States
Miklos Gellai United States
Liliana G. Bianciotti Argentina
Kimmo Kontula Finland
K. Yasunari Japan
M Böhm Germany
Kristy L. Jackson Australia
M. B. Vallotton Switzerland
Joshua S. Speed United States
H. Jin relative to Peter Rohmeiss Germany Peter Rohmeiss's profile →
Citations per field
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Citations per year

Countries citing papers authored by H. Jin

Since Specialization
Citations

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

Fields of papers citing papers by H. Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1992158
2 1990108
3 198880
4 199677
5 199258
6 199054
7 198747
8 199241
9 198831
10 199431
11 199130
12 198928
13 198824
14 199023
15 199619
16 199117
17 198817
18 199016
19 199115
20 199214

About H. Jin

H. Jin is a scholar working on Cardiology and Cardiovascular Medicine, Endocrine and Autonomic Systems, Pulmonary and Respiratory Medicine, Physiology and Cellular and Molecular Neuroscience, having authored 26 papers that have together received 928 indexed citations. Recurring topics across this work include Heart Failure Treatment and Management (7 papers), Pulmonary Hypertension Research and Treatments (5 papers), Neuropeptides and Animal Physiology (5 papers), Regulation of Appetite and Obesity (4 papers), Neuroscience of respiration and sleep (4 papers), Nitric Oxide and Endothelin Effects (3 papers), Stress Responses and Cortisol (3 papers) and Chronic Obstructive Pulmonary Disease (COPD) Research (3 papers). The work is most often cited by research in Endocrine and Autonomic Systems (148 citations), Cardiology and Cardiovascular Medicine (391 citations), Behavioral Neuroscience (53 citations), Physiology (302 citations) and Biochemistry (75 citations). H. Jin has collaborated with scholars based in United States, Australia and China. Frequent co-authors include Suzanne Oparil, Renhui Yang, J. Michael Wyss, Y F Chen, Y. F. Chen, Yen‐Fu Chen, Robert M. Jackson, Terry S. Elton, Patricia H. Hicks and George R. Taylor. Their work appears in journals such as Hypertension, Journal of Applied Physiology, Journal of Clinical Investigation, American Journal of Hypertension and Journal of Pharmacology and Experimental Therapeutics.

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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