Tianxia Lan
- Immunology top 5%
- Immunotherapy and Immune Responses 7
- Immune cells in cancer 4
- Immune Response and Inflammation 3
- Oncology top 10%
- CAR-T cell therapy research 2
- Chemokine receptors and signaling 2
- Cell Biology top 10%
- Cancer Research top 10%
- Genetics top 10%
- Virus-based gene therapy research 2
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- SARS-CoV-2 and COVID-19 Research 5
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- RNA Interference and Gene Delivery 2
- Co-authors
- Xiawei WeiMin LuoYuquan WeiMinyang FuTing LuoYuan HuKun‐Liang GuanLi Chen
- Cited by
- ImmunologyOncologyCell Biology
- Journals
- Signal Transduction and Targeted Therapy (4 papers)Acta Pharmaceutica Sinica B (2 papers)Cellular and Molecular Immunology (1 paper)
- Partner nations
- ChinaUnited StatesMacao
In The Last Decade
Tianxia Lan
23 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Immunology 461
- Oncology 391
- Cell Biology 211
- Cancer Research 185
- Genetics 113
Countries citing papers authored by Tianxia Lan
This map shows the geographic impact of Tianxia Lan'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 Tianxia Lan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tianxia Lan more than expected).
Fields of papers citing papers by Tianxia Lan
This network shows the impact of papers produced by Tianxia Lan. 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 Tianxia Lan. The network helps show where Tianxia Lan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tianxia Lan, 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 | 2024 | 4 | |
| 2 | 2024 | 4 | |
| 3 | 2023 | 21 | |
| 4 | 2023 | 35 | |
| 5 | 2023 | 2 | |
| 6 | 2022 | 31 | |
| 7 | 2022 | 22 | |
| 8 | 2022 | 20 | |
| 9 | Tumor-associated neutrophils and neutrophil-targeted cancer therapiesbreakdown → | 2022 | 187 |
| 10 | 2022 | 57 | |
| 11 | The Hippo signalling pathway and its implications in human health and diseasesbreakdown → | 2022 | 358 |
| 12 | 2022 | 22 | |
| 13 | 2022 | 5 | |
| 14 | 2022 | 78 | |
| 15 | 2021 | 14 | |
| 16 | 2021 | 8 | |
| 17 | CCL5/CCR5 axis in human diseases and related treatmentsbreakdown → | 2021 | 201 |
| 18 | Mesenchymal stem/stromal cells in cancer therapybreakdown → | 2021 | 225 |
| 19 | 2021 | 3 | |
| 20 | 2021 | 37 |
About Tianxia Lan
Tianxia Lan is a scholar working on Immunology, Oncology, Infectious Diseases, Virology and Cell Biology, having authored 23 papers that have together received 1.5k indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (7 papers), SARS-CoV-2 and COVID-19 Research (5 papers), Immune cells in cancer (4 papers), Immune Response and Inflammation (3 papers), Virus-based gene therapy research (2 papers), CAR-T cell therapy research (2 papers), RNA Interference and Gene Delivery (2 papers) and Chemokine receptors and signaling (2 papers). The work is most often cited by research in Immunology (461 citations), Oncology (391 citations), Cell Biology (211 citations), Cancer Research (185 citations) and Genetics (113 citations). Tianxia Lan has collaborated with scholars based in China, United States and Macao. Frequent co-authors include Xiawei Wei, Min Luo, Xiawei Wei, Yuquan Wei, Minyang Fu, Ting Luo, Yuan Hu, Kun‐Liang Guan, Li Chen and Zhen Zeng. Their work appears in journals such as Signal Transduction and Targeted Therapy, Acta Pharmaceutica Sinica B, Cellular and Molecular Immunology, Frontiers in Cell and Developmental Biology and ACS Nano.
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.