Tongwei Mo
Impact in
- Immunology top 2%
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
- Immunotherapy and Immune Responses
- Genetics top 2%
- Chronic Lymphocytic Leukemia Research
Papers in ⓘ
- Co-authors
- Riccardo Dalla‐Favera (15 shared papers)Qiong Shen (9 shared papers)Marie Lia (6 shared papers)Ulf Klein (6 shared papers)Giorgio Cattoretti (3 shared papers)Laura Pasqualucci (8 shared papers)Klaus Rajewsky (3 shared papers)Govind Bhagat (7 shared papers)
- Journals
- Blood (6 papers)Cancer Cell (3 papers)Cancer Discovery (1 paper)Nature Medicine (1 paper)Nature Communications (1 paper)
- Partner nations
- United StatesItaly
In The Last Decade
Tongwei Mo
15 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 85
- Immunology 1.0k
- Genetics 490
- Pathology and Forensic Medicine 673
- Cancer Research 546
- Oncology 537
Countries citing papers authored by Tongwei Mo
This map shows the geographic impact of Tongwei 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 Tongwei Mo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tongwei Mo more than expected).
Fields of papers citing papers by Tongwei Mo
This network shows the impact of papers produced by Tongwei 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 Tongwei Mo. The network helps show where Tongwei Mo may publish in the future.
Co-authors
The 25 scholars most cited alongside Tongwei Mo, 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 | The DLEU2/miR-15a/16-1 Cluster Controls B Cell Proliferation and Its Deletion Leads to Chronic Lymphocytic Leukemia Hit paper breakdown → | 2010 | 600 |
| 2 | Transcription factor IRF4 controls plasma cell differentiation and class-switch recombination Hit paper breakdown → | 2006 | 570 |
| 3 | 2015 | 312 | |
| 4 | 2005 | 271 | |
| 5 | 2010 | 208 | |
| 6 | 2015 | 183 | |
| 7 | 2017 | 151 | |
| 8 | 2011 | 52 | |
| 9 | 2023 | 8 | |
| 10 | 2005 | 3 | |
| 11 | 2008 | 2 | |
| 12 | 2024 | 1 | |
| 13 | 2006 | 1 | |
| 14 | 2009 | 1 | |
| 15 | 2011 | 1 |
About Tongwei Mo
Tongwei Mo is a scholar working on Aging, Genetics, Pathology and Forensic Medicine, Immunology and Oncology, having authored 15 papers that have together received 2.4k indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (7 papers), Chronic Lymphocytic Leukemia Research (6 papers), Ubiquitin and proteasome pathways (3 papers), Immune Cell Function and Interaction (3 papers), Protein Degradation and Inhibitors (2 papers), Galectins and Cancer Biology (2 papers), CAR-T cell therapy research (2 papers) and Epigenetics and DNA Methylation (2 papers). The work is most often cited by research in Immunology (1.0k citations), Genetics (490 citations), Pathology and Forensic Medicine (673 citations), Cancer Research (546 citations) and Oncology (537 citations). Tongwei Mo has collaborated with scholars based in United States and Italy. Frequent co-authors include Riccardo Dalla‐Favera, Qiong Shen, Marie Lia, Ulf Klein, Giorgio Cattoretti, Laura Pasqualucci, Klaus Rajewsky, Govind Bhagat, Stefano Casola and Thomas Ludwig. Their work appears in journals such as Blood, Cancer Cell, Cancer Discovery, Nature Medicine and Nature Communications.
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.