Qingda Meng
Impact in
- Oncology top 10%
- Cancer Immunotherapy and Biomarkers
- CAR-T cell therapy research
- Cancer Cells and Metastasis
- Pancreatic and Hepatic Oncology Research
- Immunology top 10%
- Immunotherapy and Immune Responses
- Immune Cell Function and Interaction
- Immune cells in cancer
Papers in
- Oncology 21
- Cancer Immunotherapy and Biomarkers 11
- CAR-T cell therapy research 9
- Pancreatic and Hepatic Oncology Research 4
- Cancer Cells and Metastasis 3
- Immunology 17
- Immunotherapy and Immune Responses 10
- Immune Cell Function and Interaction 7
- Co-authors
- Elena Rangelova (9 shared papers)Markus Maeurer (20 shared papers)Ernest Dodoo (17 shared papers)Martin Rao (13 shared papers)Zhenjiang Liu (16 shared papers)Carlos Fernández Moro (2 shared papers)Thomas Poiret (13 shared papers)Helen Kaipe (1 shared paper)
In The Last Decade
Qingda Meng
32 papers receiving 662 citations
Peers
Comparison fields: 5 of 73
- Oncology 419
- Immunology 308
- Genetics 46
- Cancer Research 54
- Biotechnology 27
Countries citing papers authored by Qingda Meng
This map shows the geographic impact of Qingda Meng'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 Qingda Meng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingda Meng more than expected).
Fields of papers citing papers by Qingda Meng
This network shows the impact of papers produced by Qingda Meng. 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 Qingda Meng. The network helps show where Qingda Meng may publish in the future.
Co-authors
The 25 scholars most cited alongside Qingda Meng, 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 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 153 | |
| 2 | 2016 | 72 | |
| 3 | 2016 | 67 | |
| 4 | 2021 | 54 | |
| 5 | 2015 | 40 | |
| 6 | 2014 | 26 | |
| 7 | 2018 | 24 | |
| 8 | 2015 | 23 | |
| 9 | 2018 | 18 | |
| 10 | 2017 | 18 | |
| 11 | 2018 | 14 | |
| 12 | 2018 | 14 | |
| 13 | 2017 | 13 | |
| 14 | 2018 | 13 | |
| 15 | 2018 | 13 | |
| 16 | 2017 | 12 | |
| 17 | Hepatic epithelioid angiomyolipoma with an unusual pathologic appearance: expanding the morphologic spectrum. | 2014 | 12 |
| 18 | 2016 | 12 | |
| 19 | 2013 | 9 | |
| 20 | 2016 | 9 |
About Qingda Meng
Qingda Meng is a scholar working on Oncology, Immunology, Pulmonary and Respiratory Medicine, Epidemiology and Surgery, having authored 36 papers that have together received 667 indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (11 papers), Immunotherapy and Immune Responses (10 papers), CAR-T cell therapy research (9 papers), Immune Cell Function and Interaction (7 papers), Cytomegalovirus and herpesvirus research (6 papers), Pancreatic and Hepatic Oncology Research (4 papers), Cancer Cells and Metastasis (3 papers) and Glioma Diagnosis and Treatment (3 papers). The work is most often cited by research in Oncology (419 citations), Immunology (308 citations), Genetics (46 citations), Cancer Research (54 citations) and Biotechnology (27 citations). Qingda Meng has collaborated with scholars based in Sweden, China and Germany. Frequent co-authors include Elena Rangelova, Markus Maeurer, Ernest Dodoo, Martin Rao, Zhenjiang Liu, Carlos Fernández Moro, Thomas Poiret, Helen Kaipe, Peter Bankhead and Laia Gorchs. Their work appears in journals such as Oncotarget, Journal for ImmunoTherapy of Cancer, Scientific Reports, Frontiers in Immunology and EBioMedicine.
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.