Hongnan Mo
- Oncology top 2%
- Pulmonary and Respiratory Medicine top 5%
- Immunology top 10%
- Molecular Biology
- Cancer Research top 5%
- Co-authors
- Peng LiuBinghe XuFei MaJing HuangDawei WuXiaoying SunBo LanXuelian Chen
- Topics
- Cancer Immunotherapy and Biomarkers (13 papers)HER2/EGFR in Cancer Research (12 papers)Advanced Breast Cancer Therapies (12 papers)
- Cited by
- OncologyCancer ResearchImmunology
- Journals
- Nature MedicineJournal of Clinical OncologySHILAP Revista de lepidopterología
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Hongnan Mo
49 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Oncology 1.0k
- Pulmonary and Respiratory Medicine 427
- Immunology 381
- Molecular Biology 372
- Cancer Research 341
Countries citing papers authored by Hongnan Mo
This map shows the geographic impact of Hongnan Mo'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 Hongnan Mo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hongnan Mo more than expected).
Fields of papers citing papers by Hongnan Mo
This network shows the impact of papers produced by Hongnan Mo. 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 Hongnan Mo. The network helps show where Hongnan Mo may publish in the future.
Co-authorship network of co-authors of Hongnan Mo
This figure shows the co-authorship network connecting the top 25 collaborators of Hongnan Mo. A scholar is included among the top collaborators of Hongnan Mo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hongnan Mo. Hongnan Mo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | Distinct cellular mechanisms underlie chemotherapies and PD-L1 blockade combinations in triple-negative breast cancerbreakdown → | 25 |
| 4 | 11 | |
| 5 | 1 | |
| 6 | 27 | |
| 7 | 26 | |
| 8 | 4 | |
| 9 | Single-cell analyses reveal key immune cell subsets associated with response to PD-L1 blockade in triple-negative breast cancerbreakdown → | 434 |
| 10 | 31 | |
| 11 | 9 | |
| 12 | 10 | |
| 13 | 14 | |
| 14 | 1 | |
| 15 | 46 | |
| 16 | 13 | |
| 17 | 149 | |
| 18 | 1 | |
| 19 | 5 | |
| 20 | 1 |
About Hongnan Mo
Hongnan Mo is a scholar working on Oncology, Cancer Research and Pulmonary and Respiratory Medicine, having authored 54 papers that have together received 1.5k indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (13 papers), HER2/EGFR in Cancer Research (12 papers) and Advanced Breast Cancer Therapies (12 papers). The work is most often cited by research in Oncology (1.0k citations), Cancer Research (341 citations) and Immunology (381 citations). Hongnan Mo has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Peng Liu, Binghe Xu, Fei Ma, Jing Huang, Dawei Wu, Xiaoying Sun, Bo Lan, Xuelian Chen, Dong Qu and Hongyan Chen. Their work appears in journals such as Nature Medicine, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.
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.