Ru Nie
Impact in
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Artificial Intelligence top 2%
- Machine Learning and ELM
Papers in
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- Circular RNAs in diseases 4
- Machine Learning in Bioinformatics 4
- Bioinformatics and Genomic Networks 3
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- MicroRNA in disease regulation 9
- Cancer-related molecular mechanisms research 8
- Co-authors
- Shifei Ding (4 shared papers)Xinzheng Xu (3 shared papers)Yanan Zhang (1 shared paper)Han Zhao (1 shared paper)Zhengwei Li (16 shared papers)Zhu‐Hong You (12 shared papers)Hongjie Jia (1 shared paper)Jiashu Li (2 shared papers)
In The Last Decade
Ru Nie
26 papers receiving 1.3k citations
Ru Nie's Hit Papers
Peers
Comparison fields: 5 of 137
- Cancer Research 213
- Artificial Intelligence 490
- Computational Theory and Mathematics 124
- Computer Vision and Pattern Recognition 143
- Molecular Biology 349
Countries citing papers authored by Ru Nie
This map shows the geographic impact of Ru 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 Ru Nie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ru Nie more than expected).
Fields of papers citing papers by Ru Nie
This network shows the impact of papers produced by Ru 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 Ru Nie. The network helps show where Ru Nie may publish in the future.
Co-authors
The 25 scholars most cited alongside Ru 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Extreme learning machine: algorithm, theory and applications Hit paper breakdown → | 2013 | 455 |
| 2 | 2013 | 254 | |
| 3 | 2013 | 150 | |
| 4 | 2020 | 99 | |
| 5 | 2017 | 70 | |
| 6 | 2022 | 62 | |
| 7 | 2021 | 38 | |
| 8 | 2016 | 29 | |
| 9 | 2020 | 23 | |
| 10 | 2017 | 21 | |
| 11 | 2022 | 17 | |
| 12 | 2023 | 9 | |
| 13 | 2024 | 7 | |
| 14 | 2024 | 6 | |
| 15 | 2013 | 6 | |
| 16 | 2019 | 5 | |
| 17 | 2010 | 5 | |
| 18 | 2024 | 4 | |
| 19 | 2010 | 4 | |
| 20 | 2009 | 4 |
About Ru Nie
Ru Nie is a scholar working on Molecular Biology, Cancer Research, Artificial Intelligence, Control and Systems Engineering and Computational Theory and Mathematics, having authored 26 papers that have together received 1.3k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (9 papers), Cancer-related molecular mechanisms research (8 papers), Circular RNAs in diseases (4 papers), Machine Learning in Bioinformatics (4 papers), Advanced Algorithms and Applications (3 papers), Machine Learning and ELM (3 papers), Bioinformatics and Genomic Networks (3 papers) and Metaheuristic Optimization Algorithms Research (3 papers). The work is most often cited by research in Cancer Research (213 citations), Artificial Intelligence (490 citations), Computational Theory and Mathematics (124 citations), Computer Vision and Pattern Recognition (143 citations) and Molecular Biology (349 citations). Ru Nie has collaborated with scholars based in China and Canada. Frequent co-authors include Shifei Ding, Xinzheng Xu, Yanan Zhang, Han Zhao, Zhengwei Li, Zhu‐Hong You, Hongjie Jia, Jiashu Li, Wenzheng Bao and Xing Chen. Their work appears in journals such as Briefings in Bioinformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Neural Computing and Applications, BMC Medical Informatics and Decision Making and Journal of Bioinformatics and Computational Biology.
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.