Gisu Eom
Impact in
- Genetics top 2%
- Genetic Associations and Epidemiology
- Genomics and Rare Diseases
- Rheumatology top 5%
- Osteoarthritis Treatment and Mechanisms
Papers in
- Genetics 26
- Genetic Associations and Epidemiology 22
- Genomics and Rare Diseases 5
- BRCA gene mutations in cancer 2
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- Blood Coagulation and Thrombosis Mechanisms 4
Gisu Eom
33 papers receiving 2.8k citations
Gisu Eom's Hit Papers
Peers
Comparison fields: 5 of 99
- Genetics 1.5k
- Rheumatology 279
- Cardiology and Cardiovascular Medicine 368
- Nephrology 114
- Hepatology 84
Countries citing papers authored by Gisu Eom
This map shows the geographic impact of Gisu Eom'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 Gisu Eom with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gisu Eom more than expected).
Fields of papers citing papers by Gisu Eom
This network shows the impact of papers produced by Gisu Eom. 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 Gisu Eom. The network helps show where Gisu Eom may publish in the future.
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All Works
Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure Hit paper breakdown → | 2020 | 611 |
| 2 | Discovery of 318 new risk loci for type 2 diabetes and related vascular outcomes among 1.4 million participants in a multi-ancestry meta-analysis Hit paper breakdown → | 2020 | 564 |
| 3 | Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations Hit paper breakdown → | 2021 | 334 |
| 4 | Advancing human genetics research and drug discovery through exome sequencing of the UK Biobank Hit paper breakdown → | 2021 | 270 |
| 5 | Genome-wide analysis provides genetic evidence that ACE2 influences COVID-19 risk and yields risk scores associated with severe disease Hit paper breakdown → | 2022 | 139 |
| 6 | 2021 | 125 | |
| 7 | 2021 | 113 | |
| 8 | 2022 | 106 | |
| 9 | 2020 | 72 | |
| 10 | 2023 | 66 | |
| 11 | A deep catalogue of protein-coding variation in 983,578 individuals Hit paper breakdown → | 2024 | 56 |
| 12 | 2022 | 43 | |
| 13 | 2019 | 38 | |
| 14 | 2020 | 31 | |
| 15 | 2021 | 27 | |
| 16 | 2024 | 27 | |
| 17 | 2020 | 24 | |
| 18 | Kidney multiome-based genetic scorecard reveals convergent coding and regulatory variants Hit paper breakdown → | 2025 | 24 |
| 19 | 2022 | 23 | |
| 20 | 2022 | 21 |
About Gisu Eom
Gisu Eom is a scholar working on Genetics, Hematology, Ophthalmology, Cardiology and Cardiovascular Medicine and Infectious Diseases, having authored 39 papers that have together received 2.8k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (22 papers), Genomics and Rare Diseases (5 papers), Blood Coagulation and Thrombosis Mechanisms (4 papers), Cardiac electrophysiology and arrhythmias (3 papers), Smoking Behavior and Cessation (2 papers), BRCA gene mutations in cancer (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers) and Bone health and osteoporosis research (1 paper). The work is most often cited by research in Genetics (1.5k citations), Rheumatology (279 citations), Cardiology and Cardiovascular Medicine (368 citations), Nephrology (114 citations) and Hepatology (84 citations). Gisu Eom has collaborated with scholars based in United States, Sweden and United Kingdom. Their work appears in journals such as Nature Genetics, Nature, Nature Communications, Journal of the American Heart Association and Communications Biology.
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.