Jun An
Impact in
-
- Probability and Risk Models
-
- CAR-T cell therapy research
Papers in
-
- Random Matrices and Applications 3
-
- Probability and Risk Models 6
- Co-authors
- Masaki Yasukawa (5 shared papers)Toshiki Ochi (5 shared papers)Kozo Nagai (4 shared papers)Junichi Mineno (4 shared papers)Kiyotaka Kuzushima (4 shared papers)Hiroshi Shiku (3 shared papers)Yuyan Zhu (8 shared papers)Meng Yu (8 shared papers)
- Journals
- International Journal of Heat and Mass Transfer (3 papers)Blood (2 papers)PLoS ONE (2 papers)Food Bioscience (1 paper)Food Chemistry (1 paper)
- Partner nations
- ChinaJapanUnited States
In The Last Decade
Jun An
43 papers receiving 825 citations
Peers
Comparison fields: 5 of 107
- Management Science and Operations Research 105
- Oncology 178
- Immunology 136
- Statistics and Probability 52
- Hematology 56
Countries citing papers authored by Jun An
This map shows the geographic impact of Jun An'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 Jun An with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun An more than expected).
Fields of papers citing papers by Jun An
This network shows the impact of papers produced by Jun An. 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 Jun An. The network helps show where Jun An may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun An, 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 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 107 | |
| 2 | 2009 | 65 | |
| 3 | 2020 | 59 | |
| 4 | 2010 | 41 | |
| 5 | 2013 | 41 | |
| 6 | 2010 | 40 | |
| 7 | 2023 | 35 | |
| 8 | 2020 | 35 | |
| 9 | 2009 | 30 | |
| 10 | 2024 | 30 | |
| 11 | 2023 | 29 | |
| 12 | 2012 | 27 | |
| 13 | 2023 | 25 | |
| 14 | 2011 | 22 | |
| 15 | 2018 | 22 | |
| 16 | 2010 | 20 | |
| 17 | 2022 | 18 | |
| 18 | 2023 | 16 | |
| 19 | 2022 | 15 | |
| 20 | 2020 | 15 |
About Jun An
Jun An is a scholar working on Statistics and Probability, Management Science and Operations Research, Cell Biology, Finance and Animal Science and Zoology, having authored 45 papers that have together received 842 indexed citations. Recurring topics across this work include Probability and Risk Models (6 papers), Heat Transfer Mechanisms (4 papers), Heat Transfer and Optimization (4 papers), Heat Transfer and Boiling Studies (4 papers), Ferroptosis and cancer prognosis (4 papers), Endoplasmic Reticulum Stress and Disease (3 papers), Random Matrices and Applications (3 papers) and Cancer Immunotherapy and Biomarkers (3 papers). The work is most often cited by research in Management Science and Operations Research (105 citations), Oncology (178 citations), Immunology (136 citations), Statistics and Probability (52 citations) and Hematology (56 citations). Jun An has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Masaki Yasukawa, Toshiki Ochi, Kozo Nagai, Junichi Mineno, Kiyotaka Kuzushima, Hiroshi Shiku, Yuyan Zhu, Meng Yu, Gongming Xin and Jingzhi Zhang. Their work appears in journals such as International Journal of Heat and Mass Transfer, Blood, PLoS ONE, Food Bioscience and Food Chemistry.
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.