Ee-chun Cheng
Impact in
- Genetics top 10%
- Mesenchymal stem cell research
- Hematology top 10%
Papers in
-
- CRISPR and Genetic Engineering 5
- Pluripotent Stem Cells Research 3
- RNA modifications and cancer 3
- Ubiquitin and proteasome pathways 2
- Genetics 4
- Co-authors
- Haifan Lin (4 shared papers)Diane S. Krause (14 shared papers)Mei Zhong (1 shared paper)Toshiaki Watanabe (1 shared paper)Matthew J. Renda (5 shared papers)Emanuela M. Bruscia (6 shared papers)Laura E. Niklason (1 shared paper)Zhaodi Gong (1 shared paper)
- Journals
- PLoS ONE (2 papers)Blood (2 papers)Developmental Cell (1 paper)Cell Reports (1 paper)Proceedings of the National Academy of Sciences (1 paper)
- Partner nations
- United StatesItalyChina
In The Last Decade
Ee-chun Cheng
18 papers receiving 756 citations
Peers
Comparison fields: 5 of 69
- Genetics 103
- Hematology 85
- Cancer Research 106
- Molecular Biology 458
- Plant Science 159
Countries citing papers authored by Ee-chun Cheng
This map shows the geographic impact of Ee-chun Cheng'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 Ee-chun Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ee-chun Cheng more than expected).
Fields of papers citing papers by Ee-chun Cheng
This network shows the impact of papers produced by Ee-chun Cheng. 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 Ee-chun Cheng. The network helps show where Ee-chun Cheng may publish in the future.
Co-authors
The 25 scholars most cited alongside Ee-chun Cheng, 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 | 2014 | 192 | |
| 2 | 2007 | 82 | |
| 3 | 2008 | 73 | |
| 4 | 2010 | 67 | |
| 5 | 2012 | 64 | |
| 6 | 2006 | 60 | |
| 7 | 2009 | 52 | |
| 8 | 2010 | 44 | |
| 9 | 2022 | 42 | |
| 10 | 2013 | 28 | |
| 11 | 2014 | 22 | |
| 12 | 2013 | 21 | |
| 13 | 2007 | 11 | |
| 14 | 2022 | 7 | |
| 15 | 2024 | 2 | |
| 16 | 2022 | 2 | |
| 17 | 2007 | 1 | |
| 18 | 2010 | 1 |
About Ee-chun Cheng
Ee-chun Cheng is a scholar working on Molecular Biology, Genetics, Pulmonary and Respiratory Medicine, Plant Science and Surgery, having authored 18 papers that have together received 771 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (5 papers), Pluripotent Stem Cells Research (3 papers), Chromosomal and Genetic Variations (3 papers), Cystic Fibrosis Research Advances (3 papers), Neonatal Respiratory Health Research (3 papers), RNA modifications and cancer (3 papers), Ubiquitin and proteasome pathways (2 papers) and Immune responses and vaccinations (2 papers). The work is most often cited by research in Genetics (103 citations), Hematology (85 citations), Cancer Research (106 citations), Molecular Biology (458 citations) and Plant Science (159 citations). Ee-chun Cheng has collaborated with scholars based in United States, Italy and China. Frequent co-authors include Haifan Lin, Diane S. Krause, Mei Zhong, Toshiaki Watanabe, Matthew J. Renda, Emanuela M. Bruscia, Laura E. Niklason, Zhaodi Gong, Stephan W. Morris and Sharon Lin. Their work appears in journals such as PLoS ONE, Blood, Developmental Cell, Cell Reports and Proceedings of the National Academy of Sciences.
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.