Dan Wang
- Genetics top 0.5%
- Virus-based gene therapy research 38
- Genetic and phenotypic traits in livestock 19
- Genetic Mapping and Diversity in Plants and Animals 17
- Molecular Biology top 1%
- CRISPR and Genetic Engineering 32
- RNA Interference and Gene Delivery 22
- Viral Infectious Diseases and Gene Expression in Insects 9
- Aging top 5%
- Cancer Research top 5%
- Cancer-related molecular mechanisms research 15
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- Cancer Research and Treatments 7
- Co-authors
- Guangping GaoPhillip W.L. TaiFeng ZhangKim M. KeelingDavid M. BedwellSvend StrandgaardJens IversenJun Xie
- Journals
- Molecular Therapy — Methods & Clinical Development (6 papers)Molecular Therapy (6 papers)Human Gene Therapy (5 papers)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Dan Wang
220 papers receiving 6.9k citations
Hit Papers
Peers
Comparison fields: 5 of 159
- Genetics 2.5k
- Business and International Management 134
- Molecular Biology 4.5k
- Aging 84
- Cancer Research 540
Countries citing papers authored by Dan Wang
This map shows the geographic impact of Dan Wang'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 Dan Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Wang more than expected).
Fields of papers citing papers by Dan Wang
This network shows the impact of papers produced by Dan Wang. 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 Dan Wang. The network helps show where Dan Wang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dan Wang, 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 | 2025 | 1 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 4 | |
| 6 | 2024 | 2 | |
| 7 | 2023 | 2 | |
| 8 | 2023 | 74 | |
| 9 | 2023 | 7 | |
| 10 | 2022 | 81 | |
| 11 | 2022 | 6 | |
| 12 | 2021 | 27 | |
| 13 | 2021 | 20 | |
| 14 | 2021 | 8 | |
| 15 | 2021 | 80 | |
| 16 | 2020 | 23 | |
| 17 | 2019 | 21 | |
| 18 | 2019 | 12 | |
| 19 | 2019 | 5 | |
| 20 | 2017 | 150 |
About Dan Wang
Dan Wang is a scholar working on Genetics, Molecular Biology and Cancer Research, having authored 233 papers that have together received 7.0k indexed citations. Recurring topics across this work include Virus-based gene therapy research (38 papers), CRISPR and Genetic Engineering (32 papers), RNA Interference and Gene Delivery (22 papers), Genetic and phenotypic traits in livestock (19 papers), Genetic Mapping and Diversity in Plants and Animals (17 papers), Cancer-related molecular mechanisms research (15 papers), Viral Infectious Diseases and Gene Expression in Insects (9 papers) and Cancer Research and Treatments (7 papers). The work is most often cited by research in Genetics (2.5k citations), Business and International Management (134 citations) and Molecular Biology (4.5k citations). Dan Wang has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Guangping Gao, Phillip W.L. Tai, Feng Zhang, Kim M. Keeling, David M. Bedwell, Svend Strandgaard, Jens Iversen, Jun Xie, Wen Xue and Chao Ning. Their work appears in journals such as Molecular Therapy — Methods & Clinical Development, Molecular Therapy, Human Gene Therapy, International Journal of Molecular Sciences and Nature Communications.
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.