Ming‐Jer Tsai
- Genetics top 0.01%
- Estrogen and related hormone effects 118
- Animal Genetics and Reproduction 27
- Genetics and Neurodevelopmental Disorders 22
- Molecular Biology top 0.05%
- RNA Research and Splicing 40
- Genomics and Chromatin Dynamics 37
- RNA and protein synthesis mechanisms 25
- Reproductive Medicine top 0.1%
- Immunology top 0.5%
- Reproductive System and Pregnancy 26
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- Pancreatic function and diabetes 36
- Co-authors
- Bert W. O’MalleySophia Y. TsaiSergio A. OñateFrancesco J. DeMayoFrancisco J. NayaYuhong QiuFred A. PereiraAustin J. Cooney
- Journals
- Proceedings of the National Academy of Sciences (37 papers)Molecular and Cellular Biology (36 papers)Journal of Biological Chemistry (31 papers)
- Partner nations
- United StatesTaiwanChina
In The Last Decade
Ming‐Jer Tsai
374 papers receiving 34.7k citations
Hit Papers
Peers
Comparison fields: 5 of 183
- Genetics 17.0k
- Molecular Biology 21.7k
- Endocrinology, Diabetes and Metabolism 4.9k
- Reproductive Medicine 2.4k
- Immunology 4.2k
Countries citing papers authored by Ming‐Jer Tsai
This map shows the geographic impact of Ming‐Jer Tsai'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 Ming‐Jer Tsai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming‐Jer Tsai more than expected).
Fields of papers citing papers by Ming‐Jer Tsai
This network shows the impact of papers produced by Ming‐Jer Tsai. 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 Ming‐Jer Tsai. The network helps show where Ming‐Jer Tsai may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ming‐Jer Tsai, 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 | 2020 | 23 | |
| 2 | 2019 | 22 | |
| 3 | 2017 | 48 | |
| 4 | 2016 | 25 | |
| 5 | Increased COUP-TFII expression in adult hearts induces mitochondrial dysfunction resulting in heart failure | 2015 | 1 |
| 6 | 2012 | 98 | |
| 7 | 2012 | 69 | |
| 8 | 2010 | 53 | |
| 9 | 2008 | 90 | |
| 10 | 2008 | 24 | |
| 11 | 2008 | 20 | |
| 12 | 2005 | 78 | |
| 13 | 2005 | 58 | |
| 14 | 2002 | 62 | |
| 15 | 2000 | 206 | |
| 16 | 1999 | 1 | |
| 17 | 1997 | 144 | |
| 18 | 1993 | 17 | |
| 19 | 1985 | 12 | |
| 20 | 1984 | 6 |
About Ming‐Jer Tsai
Ming‐Jer Tsai is a scholar working on Genetics, Molecular Biology and Endocrinology, Diabetes and Metabolism, having authored 384 papers that have together received 35.6k indexed citations. Recurring topics across this work include Estrogen and related hormone effects (118 papers), RNA Research and Splicing (40 papers), Genomics and Chromatin Dynamics (37 papers), Pancreatic function and diabetes (36 papers), Animal Genetics and Reproduction (27 papers), Reproductive System and Pregnancy (26 papers), RNA and protein synthesis mechanisms (25 papers) and Genetics and Neurodevelopmental Disorders (22 papers). The work is most often cited by research in Genetics (17.0k citations), Molecular Biology (21.7k citations) and Endocrinology, Diabetes and Metabolism (4.9k citations). Ming‐Jer Tsai has collaborated with scholars based in United States, Taiwan and China. Frequent co-authors include Bert W. O’Malley, Sophia Y. Tsai, Sergio A. Oñate, Francesco J. DeMayo, Francisco J. Naya, Yuhong Qiu, Fred A. Pereira, Austin J. Cooney, Neil J. McKenna and Jiemin Wong. Their work appears in journals such as Proceedings of the National Academy of Sciences, Molecular and Cellular Biology, Journal of Biological Chemistry, Molecular Endocrinology and Cell.
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.