Yi A. Yin
Impact in
- Aging top 10%
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
Papers in
-
- SARS-CoV-2 and COVID-19 Research 4
- COVID-19 Clinical Research Studies 2
-
- CRISPR and Genetic Engineering 10
- DNA Repair Mechanisms 8
- Fungal and yeast genetics research 3
- Co-authors
- Thomas D. Petes (6 shared papers)Jay Shendure (2 shared papers)William Stafford Noble (2 shared papers)Aaron McKenna (1 shared paper)Jacob Matthew Schreiber (1 shared paper)Wei Chen (1 shared paper)Vikram Agarwal (1 shared paper)Maximilian Haeussler (1 shared paper)
- Journals
- Nucleic Acids Research (3 papers)Genetics (2 papers)PLoS Genetics (2 papers)Molecular Cell (2 papers)中国科学通报：英文版 (1 paper)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Yi A. Yin
26 papers receiving 866 citations
Peers
Comparison fields: 5 of 92
- Aging 32
- Modeling and Simulation 66
- Molecular Biology 629
- Business and International Management 16
- Cancer Research 88
Countries citing papers authored by Yi A. Yin
This map shows the geographic impact of Yi A. Yin'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 Yi A. Yin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yi A. Yin more than expected).
Fields of papers citing papers by Yi A. Yin
This network shows the impact of papers produced by Yi A. Yin. 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 Yi A. Yin. The network helps show where Yi A. Yin may publish in the future.
Co-authors
The 25 scholars most cited alongside Yi A. Yin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 143 | |
| 2 | 2019 | 85 | |
| 3 | 2018 | 77 | |
| 4 | 2012 | 71 | |
| 5 | 2018 | 64 | |
| 6 | 2013 | 58 | |
| 7 | 2021 | 56 | |
| 8 | 2015 | 52 | |
| 9 | 2019 | 42 | |
| 10 | 2020 | 31 | |
| 11 | 2008 | 30 | |
| 12 | 2020 | 29 | |
| 13 | 2025 | 23 | |
| 14 | 2019 | 22 | |
| 15 | 2016 | 20 | |
| 16 | 2017 | 17 | |
| 17 | 2014 | 13 | |
| 18 | 2021 | 11 | |
| 19 | 2025 | 10 | |
| 20 | 2016 | 9 |
About Yi A. Yin
Yi A. Yin is a scholar working on Infectious Diseases, Molecular Biology, Cancer Research, Modeling and Simulation and Genetics, having authored 29 papers that have together received 884 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (10 papers), DNA Repair Mechanisms (8 papers), Cancer Genomics and Diagnostics (4 papers), SARS-CoV-2 and COVID-19 Research (4 papers), COVID-19 epidemiological studies (3 papers), Chromosomal and Genetic Variations (3 papers), Fungal and yeast genetics research (3 papers) and COVID-19 Clinical Research Studies (2 papers). The work is most often cited by research in Aging (32 citations), Modeling and Simulation (66 citations), Molecular Biology (629 citations), Business and International Management (16 citations) and Cancer Research (88 citations). Yi A. Yin has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Thomas D. Petes, Jay Shendure, William Stafford Noble, Aaron McKenna, Jacob Matthew Schreiber, Wei Chen, Vikram Agarwal, Maximilian Haeussler, Sarah Deng and Lorraine Symington. Their work appears in journals such as Nucleic Acids Research, Genetics, PLoS Genetics, Molecular Cell and 中国科学通报：英文版.
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.