Kai Tan
Impact in
- Aging top 2%
- Molecular Biology top 2%
- Genomics and Chromatin Dynamics
- Single-cell and spatial transcriptomics
- Epigenetics and DNA Methylation
- Bioinformatics and Genomic Networks
- RNA Research and Splicing
- RNA and protein synthesis mechanisms
Papers in
-
- Genomics and Chromatin Dynamics 23
- Single-cell and spatial transcriptomics 18
- Epigenetics and DNA Methylation 13
- Bioinformatics and Genomic Networks 12
- RNA and protein synthesis mechanisms 6
- Oncology 16
- CAR-T cell therapy research 9
- Co-authors
- Bing He (21 shared papers)Changya Chen (14 shared papers)Li Teng (7 shared papers)Long Gao (12 shared papers)Qin Zhu (8 shared papers)Nancy A. Speck (12 shared papers)Peng Gao (14 shared papers)Duygu Ucar (2 shared papers)
- Journals
- Blood (6 papers)Proceedings of the National Academy of Sciences (5 papers)Nature Communications (5 papers)Nucleic Acids Research (4 papers)Bioinformatics (4 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Kai Tan
92 papers receiving 4.1k citations
Kai Tan's Hit Papers
Peers
Comparison fields: 5 of 141
- Aging 153
- Molecular Biology 2.7k
- Hematology 345
- Immunology 649
- Cancer Research 338
Countries citing papers authored by Kai Tan
This map shows the geographic impact of Kai Tan'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 Kai Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Tan more than expected).
Fields of papers citing papers by Kai Tan
This network shows the impact of papers produced by Kai Tan. 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 Kai Tan. The network helps show where Kai Tan may publish in the future.
Co-authors
The 25 scholars most cited alongside Kai Tan, 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 100 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A lineage-resolved molecular atlas of C. elegans embryogenesis at single-cell resolution Hit paper breakdown → | 2019 | 320 |
| 2 | 2014 | 204 | |
| 3 | 2014 | 175 | |
| 4 | 2015 | 169 | |
| 5 | 2014 | 160 | |
| 6 | 2019 | 154 | |
| 7 | 2021 | 133 | |
| 8 | 2010 | 132 | |
| 9 | 2014 | 125 | |
| 10 | 2016 | 124 | |
| 11 | 2020 | 115 | |
| 12 | 2001 | 105 | |
| 13 | 2021 | 97 | |
| 14 | 2015 | 94 | |
| 15 | 2015 | 85 | |
| 16 | 2019 | 77 | |
| 17 | 2016 | 71 | |
| 18 | 2016 | 65 | |
| 19 | 2018 | 63 | |
| 20 | 2010 | 60 |
About Kai Tan
Kai Tan is a scholar working on Molecular Biology, Oncology, Immunology, Genetics and Hematology, having authored 100 papers that have together received 4.1k indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (23 papers), Single-cell and spatial transcriptomics (18 papers), Epigenetics and DNA Methylation (13 papers), Bioinformatics and Genomic Networks (12 papers), CAR-T cell therapy research (9 papers), Zebrafish Biomedical Research Applications (8 papers), RNA and protein synthesis mechanisms (6 papers) and Immune cells in cancer (5 papers). The work is most often cited by research in Aging (153 citations), Molecular Biology (2.7k citations), Hematology (345 citations), Immunology (649 citations) and Cancer Research (338 citations). Kai Tan has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Bing He, Changya Chen, Li Teng, Long Gao, Qin Zhu, Nancy A. Speck, Peng Gao, Duygu Ucar, Tao Peng and Hiram Firpi. Their work appears in journals such as Blood, Proceedings of the National Academy of Sciences, Nature Communications, Nucleic Acids Research and Bioinformatics.
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.