Joon Ha

1.0k citations
29 papers · 721 · h-index 14

Impact in

Papers in

Joon Ha

27 papers receiving 714 citations

Peers

Joon Ha
Comparison fields: 5 of 75
  • Endocrinology, Diabetes and Metabolism 399
  • Surgery 340
  • Clinical Biochemistry 37
  • Genetics 147
  • Physiology 22
Replace Seika Kato with:
Seika Kato Japan
Miyoko Saito Japan
C Scandellari Italy
Anthony H. Stonehouse United States
Melvin K. Dea United States
Melissa Meredith United States
Giorgia Tascini Italy
Ana B. Fernandes Portugal
Leslie Glass United Kingdom
S. Ishiyama‐Shigemoto Japan
Joon Ha relative to Seika Kato Japan Seika Kato's profile →
Citations per field
00.5×10×14.8×
Seika Kato · 1×
Citations per year

Countries citing papers authored by Joon Ha

Since Specialization
Citations

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

Fields of papers citing papers by Joon Ha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015176
2 201770
3 201561
4 201757
5 201652
6 202039
7 201638
8 201635
9 201528
10 201925
11 202120
12 202317
13 202216
14 202013
15 202012
16 202211
17 202011
18 201310
19 20216
20 20235

About Joon Ha

Joon Ha is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery, Molecular Biology, Epidemiology and Cognitive Neuroscience, having authored 29 papers that have together received 721 indexed citations. Recurring topics across this work include Diabetes, Cardiovascular Risks, and Lipoproteins (13 papers), Diabetes Management and Research (12 papers), Metabolism, Diabetes, and Cancer (9 papers), Pancreatic function and diabetes (8 papers), Liver Disease Diagnosis and Treatment (6 papers), Neural dynamics and brain function (5 papers), Neuroscience and Neural Engineering (3 papers) and Diabetes Treatment and Management (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (399 citations), Surgery (340 citations), Clinical Biochemistry (37 citations), Genetics (147 citations) and Physiology (22 citations). Joon Ha has collaborated with scholars based in United States, South Korea and South Africa. Frequent co-authors include Arthur Sherman, Leslie S. Satin, Peter C. Butler, Stephanie T. Chung, Richard Bertram, Joseph P. McKenna, Matthew J. Merrins, Anne E. Sumner, LILIAN MABUNDO and Alexey Kuznetsov. Their work appears in journals such as Diabetes Research and Clinical Practice, The Journal of Clinical Endocrinology & Metabolism, American Journal of Physiology-Endocrinology and Metabolism, Biophysical Journal and Endocrinology.

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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