Xin Yan
Impact in
-
- Computational Drug Discovery Methods
- Artificial Intelligence top 5%
Papers in
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- Machine Learning in Bioinformatics 12
- Bioinformatics and Genomic Networks 10
- Circular RNAs in diseases 4
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- Imbalanced Data Classification Techniques 5
- Co-authors
- Xiao Su (2 shared papers)Xiaogang Su (4 shared papers)Chih‐Ling Tsai (1 shared paper)Lei Wang (17 shared papers)Zhu‐Hong You (15 shared papers)Jian Luo (7 shared papers)Yong Zhou (5 shared papers)Shixiong Xia (5 shared papers)
- Journals
- Scientific Reports (5 papers)Sustainability (3 papers)Soft Computing (3 papers)Knowledge-Based Systems (2 papers)Journal of Theoretical Biology (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Xin Yan
54 papers receiving 1.8k citations
Xin Yan's Hit Papers
Peers
Comparison fields: 5 of 192
- Computational Theory and Mathematics 308
- Artificial Intelligence 347
- Statistics and Probability 80
- Cancer Research 132
- Molecular Biology 541
Countries citing papers authored by Xin Yan
This map shows the geographic impact of Xin Yan'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 Xin Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xin Yan more than expected).
Fields of papers citing papers by Xin Yan
This network shows the impact of papers produced by Xin Yan. 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 Xin Yan. The network helps show where Xin Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside Xin Yan, 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 61 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 385 | |
| 2 | Linear regression Hit paper breakdown → | 2012 | 356 |
| 3 | 2017 | 145 | |
| 4 | 2019 | 82 | |
| 5 | 2016 | 81 | |
| 6 | 2019 | 65 | |
| 7 | 2006 | 46 | |
| 8 | 2011 | 45 | |
| 9 | 2021 | 43 | |
| 10 | 2018 | 34 | |
| 11 | Facilitating Score and Causal Inference Trees for Large Observational Studies | 2014 | 33 |
| 12 | 2017 | 33 | |
| 13 | 2019 | 30 | |
| 14 | 2022 | 27 | |
| 15 | 2016 | 27 | |
| 16 | 2017 | 26 | |
| 17 | 2021 | 24 | |
| 18 | 2018 | 24 | |
| 19 | 2009 | 23 | |
| 20 | 2016 | 22 |
About Xin Yan
Xin Yan is a scholar working on Molecular Biology, Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Statistics and Probability, having authored 61 papers that have together received 1.8k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (12 papers), Bioinformatics and Genomic Networks (10 papers), Face and Expression Recognition (8 papers), Cancer-related molecular mechanisms research (6 papers), Computational Drug Discovery Methods (6 papers), Imbalanced Data Classification Techniques (5 papers), Statistical Methods and Inference (4 papers) and Circular RNAs in diseases (4 papers). The work is most often cited by research in Computational Theory and Mathematics (308 citations), Artificial Intelligence (347 citations), Statistics and Probability (80 citations), Cancer Research (132 citations) and Molecular Biology (541 citations). Xin Yan has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Xiao Su, Xiaogang Su, Chih‐Ling Tsai, Lei Wang, Zhu‐Hong You, Jian Luo, Yong Zhou, Shixiong Xia, Ye Tian and Xing Chen. Their work appears in journals such as Scientific Reports, Sustainability, Soft Computing, Knowledge-Based Systems and Journal of Theoretical 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.