Riga Wu
Impact in
- Genetics top 10%
- Forensic and Genetic Research
- Genetic diversity and population structure
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- Molecular Biology Techniques and Applications
- Genomics and Phylogenetic Studies
Papers in
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- Molecular Biology Techniques and Applications 16
- Genomics and Phylogenetic Studies 4
- Genetics 23
- Forensic and Genetic Research 21
- Genetic diversity and population structure 4
- Co-authors
- Hongyu Sun (32 shared papers)Ran Li (22 shared papers)Dan Peng (18 shared papers)He Qian (2 shared papers)Haixia Li (7 shared papers)Huaqiang Wu (2 shared papers)Zhiping Yu (2 shared papers)Yue Bai (2 shared papers)
In The Last Decade
Riga Wu
49 papers receiving 681 citations
Peers
Comparison fields: 5 of 95
- Genetics 289
- Molecular Biology 253
- Electrical and Electronic Engineering 202
- Materials Chemistry 145
- Transplantation 7
Countries citing papers authored by Riga Wu
This map shows the geographic impact of Riga Wu'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 Riga Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Riga Wu more than expected).
Fields of papers citing papers by Riga Wu
This network shows the impact of papers produced by Riga Wu. 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 Riga Wu. The network helps show where Riga Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Riga Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 108 | |
| 2 | 2023 | 79 | |
| 3 | 2018 | 61 | |
| 4 | 2015 | 41 | |
| 5 | 2024 | 35 | |
| 6 | 2021 | 31 | |
| 7 | 2011 | 29 | |
| 8 | 2020 | 29 | |
| 9 | 2021 | 27 | |
| 10 | 2021 | 25 | |
| 11 | 2019 | 25 | |
| 12 | 2017 | 24 | |
| 13 | 2022 | 14 | |
| 14 | 2022 | 12 | |
| 15 | 2019 | 12 | |
| 16 | 2023 | 11 | |
| 17 | 2021 | 11 | |
| 18 | 2018 | 8 | |
| 19 | 2023 | 8 | |
| 20 | 2018 | 7 |
About Riga Wu
Riga Wu is a scholar working on Molecular Biology, Genetics, Immunology, Electrical and Electronic Engineering and Ecology, having authored 49 papers that have together received 705 indexed citations. Recurring topics across this work include Forensic and Genetic Research (21 papers), Molecular Biology Techniques and Applications (16 papers), T-cell and B-cell Immunology (6 papers), Immune Cell Function and Interaction (6 papers), Genomics and Phylogenetic Studies (4 papers), Genetic diversity and population structure (4 papers), Chalcogenide Semiconductor Thin Films (3 papers) and Immunotherapy and Immune Responses (3 papers). The work is most often cited by research in Genetics (289 citations), Molecular Biology (253 citations), Electrical and Electronic Engineering (202 citations), Materials Chemistry (145 citations) and Transplantation (7 citations). Riga Wu has collaborated with scholars based in China, Germany and Singapore. Frequent co-authors include Hongyu Sun, Ran Li, Dan Peng, He Qian, Haixia Li, Huaqiang Wu, Zhiping Yu, Yue Bai, Oana Cojocaru‐Mirédin and Yuan Yu. Their work appears in journals such as International Journal of Legal Medicine, Forensic Science International Genetics, HLA, Genes and Scientific Reports.
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.