Gang Cheng
- Oncology top 2%
- Cell Biology top 2%
- Cancer Research top 5%
- Cancer, Hypoxia, and Metabolism 10
- Molecular Biology top 5%
- Bone Metabolism and Diseases 7
- Organic Chemistry top 2%
- Synthesis and biological activity 7
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- Computational Drug Discovery Methods 10
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- Medical Imaging Techniques and Applications 10
- Radiomics and Machine Learning in Medical Imaging 6
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- Lung Cancer Diagnosis and Treatment 10
- Lung Cancer Treatments and Mutations 8
- Co-authors
- Balaraman KalyanaramanJacek ZielonkaMicaël HardyOlivier OuariJoy JosephLance L. MunnRakesh K. JainMarcos López
- Cited by
- OncologyCell BiologyCancer Research
- Journals
- Chemical Reviews (1 paper)Proceedings of the National Academy of Sciences (2 papers)Journal of the American Chemical Society (3 papers)
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
Gang Cheng
168 papers receiving 6.4k citations
Hit Papers
Peers
Comparison fields: 5 of 151
- Oncology 1.3k
- Cell Biology 679
- Cancer Research 569
- Molecular Biology 2.4k
- Organic Chemistry 872
Countries citing papers authored by Gang Cheng
This map shows the geographic impact of Gang Cheng'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 Gang Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gang Cheng more than expected).
Fields of papers citing papers by Gang Cheng
This network shows the impact of papers produced by Gang Cheng. 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 Gang Cheng. The network helps show where Gang Cheng may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gang Cheng, 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 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2025 | 0 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 5 | |
| 8 | 2023 | 6 | |
| 9 | 2023 | 1 | |
| 10 | 2023 | 13 | |
| 11 | 2023 | 2 | |
| 12 | 2022 | 13 | |
| 13 | 2021 | 47 | |
| 14 | 2021 | 0 | |
| 15 | 2021 | 2 | |
| 16 | 2020 | 5 | |
| 17 | 2020 | 4 | |
| 18 | 2020 | 6 | |
| 19 | 2013 | 28 | |
| 20 | A phase III, double-blind, placebo-controlled study (RAISE) of eltrombopag for the treatment of chronic idiopathic thrombocytopenic purpura (ITP) | 2009 | 2 |
About Gang Cheng
Gang Cheng is a scholar working on Cancer Research, Oncology and Molecular Biology, having authored 185 papers that have together received 6.5k indexed citations. Recurring topics across this work include Cancer, Hypoxia, and Metabolism (10 papers), Computational Drug Discovery Methods (10 papers), Medical Imaging Techniques and Applications (10 papers), Lung Cancer Diagnosis and Treatment (10 papers), Lung Cancer Treatments and Mutations (8 papers), Bone Metabolism and Diseases (7 papers), Synthesis and biological activity (7 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). The work is most often cited by research in Oncology (1.3k citations), Cell Biology (679 citations) and Cancer Research (569 citations). Gang Cheng has collaborated with scholars based in China, United States and France. Frequent co-authors include Balaraman Kalyanaraman, Jacek Zielonka, Micaël Hardy, Olivier Ouari, Joy Joseph, Lance L. Munn, Rakesh K. Jain, Marcos López, Adam Sikora and Janet M. Tse. Their work appears in journals such as Chemical Reviews, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.
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.