Ying Ma
- Immunology top 5%
- Mast cells and histamine 6
- Phagocytosis and Immune Regulation 5
- Oncology top 5%
- Pancreatic and Hepatic Oncology Research 5
- Cancer Research top 5%
- Molecular Biology top 10%
- RNA modifications and cancer 7
- Epigenetics and DNA Methylation 6
- Cell Biology top 10%
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- Ferroptosis and cancer prognosis 5
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- Radiomics and Machine Learning in Medical Imaging 5
- MRI in cancer diagnosis 4
- Co-authors
- Stephen E. UllrichCraig D. LogsdonHuamin WangRosa F. HwangPatrick HwuJames L. AbbruzzeseBaoan JiDavid Z. Chang
- Cited by
- ImmunologyOncologyCancer Research
- Journals
- Clinical Cancer Research (3 papers)Journal of Leukocyte Biology (2 papers)Cancer Letters (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Ying Ma
75 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 105
- Immunology 480
- Oncology 620
- Cancer Research 310
- Molecular Biology 741
- Cell Biology 124
Countries citing papers authored by Ying Ma
This map shows the geographic impact of Ying Ma'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 Ying Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying Ma more than expected).
Fields of papers citing papers by Ying Ma
This network shows the impact of papers produced by Ying Ma. 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 Ying Ma. The network helps show where Ying Ma may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ying Ma, 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 | 2026 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 3 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 3 | |
| 8 | 2023 | 3 | |
| 9 | 2023 | 43 | |
| 10 | 2023 | 2 | |
| 11 | 2018 | 110 | |
| 12 | 2018 | 68 | |
| 13 | 2018 | 4 | |
| 14 | 2013 | 161 | |
| 15 | 2011 | 119 | |
| 16 | Cinobufacini Injection Treatment of advanced Primary Liver Cancer Clinical Observation | 2010 | 2 |
| 17 | [Expression of maspin and its relation to tumor vascularization in epithelian ovarian cancer]. | 2009 | 2 |
| 18 | 2007 | 56 | |
| 19 | 2007 | 74 | |
| 20 | [TPX2 expression and its significance in squamous cell carcinoma of lung]. | 2006 | 6 |
About Ying Ma
Ying Ma is a scholar working on Microbiology, Physiology, Cancer Research, Immunology and Obstetrics and Gynecology, having authored 81 papers that have together received 1.7k indexed citations. Recurring topics across this work include RNA modifications and cancer (7 papers), Mast cells and histamine (6 papers), Epigenetics and DNA Methylation (6 papers), Pancreatic and Hepatic Oncology Research (5 papers), Ferroptosis and cancer prognosis (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Phagocytosis and Immune Regulation (5 papers) and MRI in cancer diagnosis (4 papers). The work is most often cited by research in Immunology (480 citations), Oncology (620 citations), Cancer Research (310 citations), Molecular Biology (741 citations) and Cell Biology (124 citations). Ying Ma has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Stephen E. Ullrich, Craig D. Logsdon, Huamin Wang, Rosa F. Hwang, Patrick Hwu, James L. Abbruzzese, Baoan Ji, David Z. Chang, Yanning Gao and Shujun Cheng. Their work appears in journals such as Clinical Cancer Research, Journal of Leukocyte Biology, Cancer Letters, Journal of Hematology & Oncology and iScience.
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.