Ding Ma

487 citations
9 papers · 324 · h-index 7

Impact in

    • Breast Cancer Treatment Studies
    • Cancer Genomics and Diagnostics
    • HER2/EGFR in Cancer Research
    • Cancer Immunotherapy and Biomarkers
    • Cancer Cells and Metastasis

Papers in

    • Breast Cancer Treatment Studies 6
    • Cancer, Lipids, and Metabolism 1
    • HER2/EGFR in Cancer Research 3
    • Cancer Immunotherapy and Biomarkers 1

Ding Ma

8 papers receiving 319 citations

Peers

Ding Ma
Comparison fields: 5 of 42
  • Cancer Research 120
  • Oncology 92
  • Health Informatics 8
  • Radiology, Nuclear Medicine and Imaging 27
  • Pulmonary and Respiratory Medicine 32
Replace Cheukfai Li with:
Cheukfai Li China
Valerie Cui Yun Koh Singapore
Giulia Cursano Italy
Liantao Guo China
Min-Ki Seong South Korea
Kangsan Kim United States
Evelyn Yi Ting Wong Singapore
Elizabeth Moses United States
Chiara Frascarelli Italy
Haoyang Mi United States
Ding Ma relative to Cheukfai Li China Cheukfai Li's profile →
Citations per field
00.5×2×3×3.8×
Cheukfai Li · 1×
Citations per year

Countries citing papers authored by Ding Ma

Since Specialization
Citations

This map shows the geographic impact of Ding 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 Ding Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ding Ma more than expected).

Fields of papers citing papers by Ding Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ding 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 Ding Ma. The network helps show where Ding Ma may publish in the future.

Co-authors

The 25 scholars most cited alongside Ding Ma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ding Ma Line = papers co-authored together Ding Ma links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 202383
2 202470
3 202352
4 202345
5 202434
6 202321
7 202518
8 20241
9 20260

About Ding Ma

Ding Ma is a scholar working on Cancer Research, Oncology, Artificial Intelligence, Pulmonary and Respiratory Medicine and Molecular Biology, having authored 9 papers that have together received 324 indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (6 papers), HER2/EGFR in Cancer Research (3 papers), AI in cancer detection (2 papers), Cancer, Lipids, and Metabolism (1 paper), Single-cell and spatial transcriptomics (1 paper), Advanced Breast Cancer Therapies (1 paper) and Cancer Immunotherapy and Biomarkers (1 paper). The work is most often cited by research in Cancer Research (120 citations), Oncology (92 citations), Health Informatics (8 citations), Radiology, Nuclear Medicine and Imaging (27 citations) and Pulmonary and Respiratory Medicine (32 citations). Ding Ma has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xi Jin, Yi‐Zhou Jiang, Zhi‐Ming Shao, Yi Xiao, Wentao Yang, Shen Zhao, Cai‐Jin Lin, Yi-Fan Zhou, Lei-Jie Dai and Yiyu Chen. Their work appears in journals such as Nature Communications, Cancer Research, Nature Cancer, Signal Transduction and Targeted Therapy and Cancer Biology and Medicine.

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.

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