Gang Chen
- Molecular Biology top 1%
- Pulmonary and Respiratory Medicine top 0.5%
- Oncology top 1%
- Cancer Research top 0.5%
- Surgery top 2%
- Co-authors
- Richard PazdurMartin H. CohenAtiqur RahmanGrant A. WilliamsRajeshwari SridharaGrant WilliamsShun‐Zhang YuTomoaki Tsutsumi
- Topics
- Lung Cancer Treatments and Mutations (53 papers)Lung Cancer Diagnosis and Treatment (37 papers)MicroRNA in disease regulation (31 papers)
- Journals
- Proceedings of the National Academy of SciencesNucleic Acids ResearchJournal of Biological Chemistry
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Gang Chen
545 papers receiving 12.0k citations
Hit Papers
Peers
Comparison fields: 5 of 189
- Molecular Biology 4.3k
- Pulmonary and Respiratory Medicine 2.4k
- Oncology 2.4k
- Cancer Research 1.8k
- Surgery 1.6k
Countries citing papers authored by Gang Chen
This map shows the geographic impact of Gang Chen'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 Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gang Chen more than expected).
Fields of papers citing papers by Gang Chen
This network shows the impact of papers produced by Gang Chen. 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 Chen. The network helps show where Gang Chen may publish in the future.
Co-authorship network of co-authors of Gang Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Gang Chen. A scholar is included among the top collaborators of Gang Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gang Chen. Gang Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 13 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | 6 | |
| 10 | 12 | |
| 11 | 0 | |
| 12 | Identification Prognostic Value and Correlation with Tumor-Infiltrating Immune Cells of Tripartite-Motif Family Genes in Hepatocellular Carcinoma | 10 |
| 13 | 1 | |
| 14 | 3 | |
| 15 | 38 | |
| 16 | 23 | |
| 17 | 38 | |
| 18 | 42 | |
| 19 | 11 | |
| 20 | [Retrospective analysis of 4 cases of the so-called blastic NK-cell lymphoma, with reference to the 2008 WHO classification of tumours of haematopoietic and lymphoid tissues]. | 4 |
About Gang Chen
Gang Chen is a scholar working on Cancer Research, Pulmonary and Respiratory Medicine and Oncology, having authored 576 papers that have together received 12.3k indexed citations. Recurring topics across this work include Lung Cancer Treatments and Mutations (53 papers), Lung Cancer Diagnosis and Treatment (37 papers) and MicroRNA in disease regulation (31 papers). The work is most often cited by research in Cancer Research (1.8k citations), Oncology (2.4k citations) and Pulmonary and Respiratory Medicine (2.4k citations). Gang Chen has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Richard Pazdur, Martin H. Cohen, Atiqur Rahman, Grant A. Williams, Rajeshwari Sridhara, Grant Williams, Shun‐Zhang Yu, Tomoaki Tsutsumi, Yoshio Ueno and Satoshi Nagata. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.
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.