Bin Zhang
- Cancer Research top 0.2%
- MicroRNA in disease regulation 46
- Cancer, Hypoxia, and Metabolism 16
- Cancer-related molecular mechanisms research 15
- Genetics top 0.5%
- Mesenchymal stem cell research 20
- Molecular Biology top 0.5%
- Extracellular vesicles in disease 42
- Circular RNAs in diseases 28
- RNA Interference and Gene Delivery 10
- Rehabilitation top 0.5%
- Immunology top 2%
-
- Autophagy in Disease and Therapy 11
- Journals
- Journal of Biological Chemistry (1 paper)Nature Genetics (1 paper)Journal of Clinical Oncology (3 papers)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Bin Zhang
174 papers receiving 9.0k citations
Hit Papers
Peers
Comparison fields: 5 of 134
- Cancer Research 3.4k
- Genetics 1.6k
- Molecular Biology 6.3k
- Rehabilitation 504
- Immunology 1.4k
Countries citing papers authored by Bin Zhang
This map shows the geographic impact of Bin Zhang'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 Bin Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bin Zhang more than expected).
Fields of papers citing papers by Bin Zhang
This network shows the impact of papers produced by Bin Zhang. 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 Bin Zhang. The network helps show where Bin Zhang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Bin Zhang, 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 | 1 | |
| 2 | 2023 | 16 | |
| 3 | 2023 | 13 | |
| 4 | 2023 | 2 | |
| 5 | 2023 | 12 | |
| 6 | 2022 | 27 | |
| 7 | 2021 | 29 | |
| 8 | Mesenchymal stem cell-derived exosomes: a promising vector in treatment for diabetes and its microvascular complications. | 2021 | 8 |
| 9 | 2020 | 10 | |
| 10 | 2020 | 19 | |
| 11 | 2020 | 42 | |
| 12 | 2019 | 52 | |
| 13 | 2019 | 14 | |
| 14 | 2019 | 26 | |
| 15 | 2019 | 10 | |
| 16 | 2018 | 36 | |
| 17 | Human Mesenchymal Stem Cell Derived Exosomes Alleviate Type 2 Diabetes Mellitus by Reversing Peripheral Insulin Resistance and Relieving β-Cell Destructionbreakdown → | 2018 | 354 |
| 18 | 2017 | 1 | |
| 19 | 2012 | 67 | |
| 20 | 2006 | 373 |
About Bin Zhang
Bin Zhang is a scholar working on Cancer Research, Genetics and Cell Biology, having authored 177 papers that have together received 9.1k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (46 papers), Extracellular vesicles in disease (42 papers), Circular RNAs in diseases (28 papers), Mesenchymal stem cell research (20 papers), Cancer, Hypoxia, and Metabolism (16 papers), Cancer-related molecular mechanisms research (15 papers), Autophagy in Disease and Therapy (11 papers) and RNA Interference and Gene Delivery (10 papers). The work is most often cited by research in Cancer Research (3.4k citations), Genetics (1.6k citations) and Molecular Biology (6.3k citations). Bin Zhang has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Hui Qian, Wenrong Xu, Sai Kiang Lim, Ruenn Chai Lai, Xu Zhang, Hui Shi, Yongmin Yan, Wei Zhu, Ronne Wee Yeh Yeo and Yijun Yin. Their work appears in journals such as Journal of Biological Chemistry, Nature Genetics and Journal of Clinical Oncology.
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.