Hangil Chang

18 papers receiving 610 citations

Peers

Hangil Chang
Comparison fields: 5 of 75
  • Nephrology 185
  • Nutrition and Dietetics 112
  • Biochemistry 41
  • Molecular Biology 342
  • Endocrinology, Diabetes and Metabolism 73
Replace Lisa Mastrofrancesco with:
Lisa Mastrofrancesco Italy
Hiroko Yasuda Japan
Alia Shatanawi Jordan
Yuzhou Xiao China
Zhipeng Feng China
An Xie China
Shohei Kinoshita Japan
Dmytro O. Kryshtal United States
Kamiar Mohammadi France
Ewa Jasek-Gajda Poland
Hangil Chang relative to Lisa Mastrofrancesco Italy Lisa Mastrofrancesco's profile →
Citations per field
00.5×8.2×
Lisa Mastrofrancesco · 1×
Citations per year

Countries citing papers authored by Hangil Chang

Since Specialization
Citations

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

Fields of papers citing papers by Hangil Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 2002272
2 199062
3 200761
4 200535
5 199525
6 199925
7 199623
8 199623
9 199123
10 200120
11 199917
12 200116
13 199510
14 199610
15 19883
16 19953
17 19851
18 19961

About Hangil Chang

Hangil Chang is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Pulmonary and Respiratory Medicine, Nephrology and Cardiology and Cardiovascular Medicine, having authored 18 papers that have together received 630 indexed citations. Recurring topics across this work include Ion Transport and Channel Regulation (6 papers), Ion channel regulation and function (5 papers), Electrolyte and hormonal disorders (3 papers), Neuroscience and Neuropharmacology Research (3 papers), Cardiac electrophysiology and arrhythmias (2 papers), Nitric Oxide and Endothelin Effects (2 papers), Liver Disease and Transplantation (1 paper) and Machine Learning in Bioinformatics (1 paper). The work is most often cited by research in Nephrology (185 citations), Nutrition and Dietetics (112 citations), Biochemistry (41 citations), Molecular Biology (342 citations) and Endocrinology, Diabetes and Metabolism (73 citations). Hangil Chang has collaborated with scholars based in Japan, South Korea and United Kingdom. Frequent co-authors include Toshiro Fujita, Ryo Okazaki, Sumiyo Watanabe, Seiji Fukumoto, Yukihiro Hasegawa, Yasuhiro Takeuchi, Noriko Chikatsu, Kiyoshi Kurokawa, Takatoshi Okuda and Hyun Joon Kim. Their work appears in journals such as American Journal of Physiology-Renal Physiology, Biochemical and Biophysical Research Communications, Pflügers Archiv - European Journal of Physiology, The Journal of Membrane Biology and Journal of Hypertension.

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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