Yan Liang
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- Cancer Immunotherapy and Biomarkers 7
- CAR-T cell therapy research 5
- Cancer Cells and Metastasis 4
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- Single-cell and spatial transcriptomics 9
- Advanced Biosensing Techniques and Applications 5
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- Sarcoma Diagnosis and Treatment 10
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- Cancer Research and Treatments 7
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- Glioma Diagnosis and Treatment 4
- Cited by
- OncologyImmunologyCancer Research
- Journals
- Journal of Clinical Oncology (4 papers)SHILAP Revista de lepidopterología (2 papers)Blood (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Yan Liang
65 papers receiving 683 citations
Peers
Comparison fields: 5 of 84
- Oncology 172
- Immunology 127
- Cancer Research 80
- Molecular Biology 353
- Neurology 38
Countries citing papers authored by Yan Liang
This map shows the geographic impact of Yan Liang'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 Yan Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yan Liang more than expected).
Fields of papers citing papers by Yan Liang
This network shows the impact of papers produced by Yan Liang. 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 Yan Liang. The network helps show where Yan Liang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yan Liang, 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 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 3 | |
| 6 | 2022 | 14 | |
| 7 | 2022 | 4 | |
| 8 | 2021 | 10 | |
| 9 | 2021 | 24 | |
| 10 | 2021 | 6 | |
| 11 | 2021 | 1 | |
| 12 | 2019 | 96 | |
| 13 | 2019 | 41 | |
| 14 | 2017 | 2 | |
| 15 | 2016 | 5 | |
| 16 | Expression of hypoxia-inducible factor-1 alpha,hexokinase-II and lactate dehydrogenase-V in hepatocellular carcinoma and their biological significance | 2013 | 1 |
| 17 | Retrospective Cohort Study on Clinical Value of Huaier Granule in Postoperative Patients with Liver Transplantation for Hepatocellular Carcinoma | 2010 | 4 |
| 18 | 2006 | 53 | |
| 19 | The feasibility of a new clinical staging for primary liver cancer | 2001 | 1 |
| 20 | [Expression of bcl-2, bax and p53 protein in the basal cell carcinoma]. | 1999 | 4 |
About Yan Liang
Yan Liang is a scholar working on Oncology, Biotechnology and Health Informatics, having authored 71 papers that have together received 687 indexed citations. Recurring topics across this work include Sarcoma Diagnosis and Treatment (10 papers), Single-cell and spatial transcriptomics (9 papers), Cancer Research and Treatments (7 papers), Cancer Immunotherapy and Biomarkers (7 papers), CAR-T cell therapy research (5 papers), Advanced Biosensing Techniques and Applications (5 papers), Glioma Diagnosis and Treatment (4 papers) and Cancer Cells and Metastasis (4 papers). The work is most often cited by research in Oncology (172 citations), Immunology (127 citations) and Cancer Research (80 citations). Yan Liang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xiuyun Tian, Chunyi Hao, Xiaoya Guan, Chang-Qing Deng, Hua Li, Shuping Zhang, Xiyun Yan, Bing Jiang, Bin Dong and Min Zhao. Their work appears in journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Blood.
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.