Lingyun Long
Impact in
- Immunology top 2%
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
- Immune cells in cancer
- Immunotherapy and Immune Responses
- Cancer Research top 5%
- Cancer, Hypoxia, and Metabolism
Papers in
-
- CRISPR and Genetic Engineering 3
- Wnt/β-catenin signaling in development and cancer 2
- Photosynthetic Processes and Mechanisms 2
- Immunology 13
- T-cell and B-cell Immunology 6
- Immune Cell Function and Interaction 6
- Immune cells in cancer 3
- Co-authors
- Hongbo Chi (11 shared papers)Jun Wei (7 shared papers)Peter Vogel (6 shared papers)Yogesh Dhungana (8 shared papers)Nicole M. Chapman (5 shared papers)Cliff Guy (5 shared papers)Geoffrey Neale (4 shared papers)Jordy Saravia (4 shared papers)
- Journals
- Nature (3 papers)Cell Research (2 papers)Immunity (2 papers)Cell Metabolism (1 paper)Blood (1 paper)
- Partner nations
- United StatesChinaSingapore
In The Last Decade
Lingyun Long
25 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 99
- Immunology 1.1k
- Cancer Research 403
- Oncology 611
- Molecular Biology 978
- Physiology 61
Countries citing papers authored by Lingyun Long
This map shows the geographic impact of Lingyun Long'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 Lingyun Long with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lingyun Long more than expected).
Fields of papers citing papers by Lingyun Long
This network shows the impact of papers produced by Lingyun Long. 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 Lingyun Long. The network helps show where Lingyun Long may publish in the future.
Co-authors
The 25 scholars most cited alongside Lingyun Long, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 348 | |
| 2 | Lipid signalling enforces functional specialization of Treg cells in tumours Hit paper breakdown → | 2021 | 286 |
| 3 | 2019 | 281 | |
| 4 | 2011 | 208 | |
| 5 | 2017 | 152 | |
| 6 | 2020 | 129 | |
| 7 | 2014 | 101 | |
| 8 | 2019 | 97 | |
| 9 | 2021 | 95 | |
| 10 | 2012 | 89 | |
| 11 | 2023 | 64 | |
| 12 | 2015 | 63 | |
| 13 | 2021 | 61 | |
| 14 | 2015 | 56 | |
| 15 | 2019 | 53 | |
| 16 | 2013 | 43 | |
| 17 | 2017 | 40 | |
| 18 | 2020 | 39 | |
| 19 | 2016 | 27 | |
| 20 | 2021 | 25 |
About Lingyun Long
Lingyun Long is a scholar working on Molecular Biology, Immunology, Oncology, Genetics and Epidemiology, having authored 27 papers that have together received 2.3k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (6 papers), Immune Cell Function and Interaction (6 papers), CRISPR and Genetic Engineering (3 papers), Immune cells in cancer (3 papers), Plant Molecular Biology Research (2 papers), Wnt/β-catenin signaling in development and cancer (2 papers), CAR-T cell therapy research (2 papers) and Photosynthetic Processes and Mechanisms (2 papers). The work is most often cited by research in Immunology (1.1k citations), Cancer Research (403 citations), Oncology (611 citations), Molecular Biology (978 citations) and Physiology (61 citations). Lingyun Long has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Hongbo Chi, Jun Wei, Peter Vogel, Yogesh Dhungana, Nicole M. Chapman, Cliff Guy, Geoffrey Neale, Jordy Saravia, Hongling Huang and Kai Yang. Their work appears in journals such as Nature, Cell Research, Immunity, Cell Metabolism and Blood.
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.