Kui Nie
Impact in
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Cancer Genomics and Diagnostics
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- Lymphoma Diagnosis and Treatment
Papers in
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- Lymphoma Diagnosis and Treatment 14
-
- Glycosylation and Glycoproteins Research 3
- Cancer-related gene regulation 3
- Co-authors
- Wayne Tam (15 shared papers)Daniel M. Knowles (6 shared papers)Olivier Elemento (7 shared papers)David Redmond (7 shared papers)Shijun Hu (6 shared papers)Zuoyong Zhou (6 shared papers)Yanwen Jiang (5 shared papers)Leonard Tan (4 shared papers)
- Journals
- Blood (6 papers)Experimental Parasitology (2 papers)American Journal Of Pathology (2 papers)American Journal of Clinical Pathology (2 papers)Journal of Visualized Experiments (2 papers)
- Partner nations
- ChinaUnited StatesItaly
In The Last Decade
Kui Nie
29 papers receiving 682 citations
Peers
Comparison fields: 5 of 72
- Cancer Research 172
- Pathology and Forensic Medicine 189
- Parasitology 71
- Genetics 82
- Animal Science and Zoology 85
Countries citing papers authored by Kui Nie
This map shows the geographic impact of Kui Nie'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 Kui Nie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kui Nie more than expected).
Fields of papers citing papers by Kui Nie
This network shows the impact of papers produced by Kui Nie. 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 Kui Nie. The network helps show where Kui Nie may publish in the future.
Co-authors
The 25 scholars most cited alongside Kui Nie, 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 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 134 | |
| 2 | 2015 | 95 | |
| 3 | 2014 | 65 | |
| 4 | 2010 | 50 | |
| 5 | 2017 | 46 | |
| 6 | 2013 | 45 | |
| 7 | 2014 | 44 | |
| 8 | 2010 | 36 | |
| 9 | 2010 | 31 | |
| 10 | 2021 | 24 | |
| 11 | 2012 | 15 | |
| 12 | 2015 | 14 | |
| 13 | 2009 | 12 | |
| 14 | 2017 | 11 | |
| 15 | 2018 | 10 | |
| 16 | 2011 | 9 | |
| 17 | 2023 | 9 | |
| 18 | 2014 | 9 | |
| 19 | 2015 | 8 | |
| 20 | 2024 | 6 |
About Kui Nie
Kui Nie is a scholar working on Pathology and Forensic Medicine, Molecular Biology, Animal Science and Zoology, Small Animals and Electrical and Electronic Engineering, having authored 31 papers that have together received 685 indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (14 papers), Coccidia and coccidiosis research (7 papers), Veterinary medicine and infectious diseases (5 papers), Animal Nutrition and Physiology (4 papers), Glycosylation and Glycoproteins Research (3 papers), Cancer-related gene regulation (3 papers), Advanced Photocatalysis Techniques (2 papers) and Vector-borne infectious diseases (2 papers). The work is most often cited by research in Cancer Research (172 citations), Pathology and Forensic Medicine (189 citations), Parasitology (71 citations), Genetics (82 citations) and Animal Science and Zoology (85 citations). Kui Nie has collaborated with scholars based in China, United States and Italy. Frequent co-authors include Wayne Tam, Daniel M. Knowles, Olivier Elemento, David Redmond, Shijun Hu, Zuoyong Zhou, Yanwen Jiang, Leonard Tan, Ari Melnick and Amy Chadburn. Their work appears in journals such as Blood, Experimental Parasitology, American Journal Of Pathology, American Journal of Clinical Pathology and Journal of Visualized Experiments.
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.