Ruihan Yang
Impact in
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- Computational Drug Discovery Methods
Papers in
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- Music Technology and Sound Studies 3
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- Robot Manipulation and Learning 4
- Co-authors
- Yong‐Huan Yun (2 shared papers)Hongmei Lü (2 shared papers)Ming Wen (2 shared papers)Shaoyu Niu (1 shared paper)Haozhi Sha (1 shared paper)Zhimin Zhang (1 shared paper)Stephan Mandt (3 shared papers)Yoshitomo Matsubara (1 shared paper)
- Journals
- Critical Reviews in Oncology/Hematology (1 paper)International Immunopharmacology (1 paper)BMC Oral Health (1 paper)Atmospheric Environment (1 paper)Advanced Healthcare Materials (1 paper)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Ruihan Yang
28 papers receiving 644 citations
Ruihan Yang's Hit Papers
Peers
Comparison fields: 5 of 100
- Computational Theory and Mathematics 338
- Health Informatics 6
- Biophysics 26
- Molecular Biology 283
- Computer Vision and Pattern Recognition 74
Countries citing papers authored by Ruihan Yang
This map shows the geographic impact of Ruihan Yang'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 Ruihan Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ruihan Yang more than expected).
Fields of papers citing papers by Ruihan Yang
This network shows the impact of papers produced by Ruihan Yang. 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 Ruihan Yang. The network helps show where Ruihan Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Ruihan Yang, 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Deep-Learning-Based Drug–Target Interaction Prediction Hit paper breakdown → | 2017 | 423 |
| 2 | 2022 | 46 | |
| 3 | 2024 | 31 | |
| 4 | 2016 | 24 | |
| 5 | 2023 | 18 | |
| 6 | 2024 | 16 | |
| 7 | 2022 | 14 | |
| 8 | 2022 | 14 | |
| 9 | 2023 | 13 | |
| 10 | 2023 | 8 | |
| 11 | 2023 | 8 | |
| 12 | 2022 | 5 | |
| 13 | 2022 | 4 | |
| 14 | 2019 | 4 | |
| 15 | 2024 | 4 | |
| 16 | 2021 | 3 | |
| 17 | 2023 | 3 | |
| 18 | 2023 | 3 | |
| 19 | 2024 | 2 | |
| 20 | 2023 | 2 |
About Ruihan Yang
Ruihan Yang is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering, Artificial Intelligence, Molecular Biology and Cognitive Neuroscience, having authored 32 papers that have together received 655 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (4 papers), Music Technology and Sound Studies (3 papers), Immune cells in cancer (2 papers), Music and Audio Processing (2 papers), Neuroscience and Music Perception (2 papers), Robotic Locomotion and Control (2 papers), Vehicle emissions and performance (1 paper) and Zeolite Catalysis and Synthesis (1 paper). The work is most often cited by research in Computational Theory and Mathematics (338 citations), Health Informatics (6 citations), Biophysics (26 citations), Molecular Biology (283 citations) and Computer Vision and Pattern Recognition (74 citations). Ruihan Yang has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Yong‐Huan Yun, Hongmei Lü, Ming Wen, Shaoyu Niu, Haozhi Sha, Zhimin Zhang, Stephan Mandt, Yoshitomo Matsubara, Marco Levorato and Xiaolong Wang. Their work appears in journals such as Critical Reviews in Oncology/Hematology, International Immunopharmacology, BMC Oral Health, Atmospheric Environment and Advanced Healthcare Materials.
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.