Git Chung
Impact in
- Pharmacology top 10%
- Pharmacogenetics and Drug Metabolism
-
- Chronic Kidney Disease and Diabetes
Papers in
- Oncology 7
- Drug Transport and Resistance Mechanisms 7
-
- Retinal Development and Disorders 2
- Co-authors
- Colin Brown (9 shared papers)Sarah Jenkinson (1 shared paper)Caroline Lee (2 shared papers)Bhagwat Prasad (1 shared paper)Jonathan Himmelfarb (1 shared paper)Katherine Johnson (1 shared paper)Sarah Billington (1 shared paper)Edward J. Kelly (1 shared paper)
- Journals
- Drug Metabolism and Disposition (2 papers)iScience (1 paper)Toxicological Sciences (1 paper)Pflügers Archiv - European Journal of Physiology (1 paper)Journal of Pharmacology and Experimental Therapeutics (1 paper)
- Partner nations
- United KingdomUnited StatesIndia
In The Last Decade
Git Chung
13 papers receiving 372 citations
Peers
Comparison fields: 5 of 75
- Pharmacology 62
- Nephrology 37
- Oncology 142
- Pediatrics, Perinatology and Child Health 91
- Transplantation 12
Countries citing papers authored by Git Chung
This map shows the geographic impact of Git Chung'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 Git Chung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Git Chung more than expected).
Fields of papers citing papers by Git Chung
This network shows the impact of papers produced by Git Chung. 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 Git Chung. The network helps show where Git Chung may publish in the future.
Co-authors
The 25 scholars most cited alongside Git Chung, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 149 | |
| 2 | 2016 | 114 | |
| 3 | 2020 | 22 | |
| 4 | 2023 | 21 | |
| 5 | 2013 | 17 | |
| 6 | 2021 | 15 | |
| 7 | 2018 | 14 | |
| 8 | 2020 | 11 | |
| 9 | 2018 | 8 | |
| 10 | 2022 | 4 | |
| 11 | 2023 | 3 | |
| 12 | 2022 | 2 | |
| 13 | Enhancing immune function of hiPSC-derived retinal organoids by incorporating microglial cells | 2020 | 1 |
| 14 | 2025 | 0 |
About Git Chung
Git Chung is a scholar working on Oncology, Molecular Biology, Pediatrics, Perinatology and Child Health, Clinical Biochemistry and Pharmacology, having authored 14 papers that have together received 381 indexed citations. Recurring topics across this work include Drug Transport and Resistance Mechanisms (7 papers), Metabolism and Genetic Disorders (3 papers), Pharmacological Effects and Toxicity Studies (3 papers), Pharmacogenetics and Drug Metabolism (2 papers), Retinal Diseases and Treatments (2 papers), Retinal Development and Disorders (2 papers), Nanoplatforms for cancer theranostics (1 paper) and Antibiotics Pharmacokinetics and Efficacy (1 paper). The work is most often cited by research in Pharmacology (62 citations), Nephrology (37 citations), Oncology (142 citations), Pediatrics, Perinatology and Child Health (91 citations) and Transplantation (12 citations). Git Chung has collaborated with scholars based in United Kingdom, United States and India. Frequent co-authors include Colin Brown, Sarah Jenkinson, Caroline Lee, Bhagwat Prasad, Jonathan Himmelfarb, Katherine Johnson, Sarah Billington, Edward J. Kelly, Jashvant D. Unadkat and Lyle Armstrong. Their work appears in journals such as Drug Metabolism and Disposition, iScience, Toxicological Sciences, Pflügers Archiv - European Journal of Physiology 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.