Yansen Su
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods 14
- Artificial Intelligence top 1%
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- Complex Network Analysis Techniques 10
- Information Systems top 2%
- Molecular Biology top 10%
- Gene expression and cancer classification 18
- Bioinformatics and Genomic Networks 18
- Single-cell and spatial transcriptomics 13
- Gene Regulatory Network Analysis 12
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- Cancer-related molecular mechanisms research 11
- MicroRNA in disease regulation 9
In The Last Decade
Yansen Su
96 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 139
- Computational Theory and Mathematics 906
- Artificial Intelligence 1.1k
- Statistical and Nonlinear Physics 262
- Information Systems 290
- Molecular Biology 746
Countries citing papers authored by Yansen Su
This map shows the geographic impact of Yansen Su'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 Yansen Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yansen Su more than expected).
Fields of papers citing papers by Yansen Su
This network shows the impact of papers produced by Yansen Su. 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 Yansen Su. The network helps show where Yansen Su may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yansen Su, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 5 | |
| 4 | 2023 | 8 | |
| 5 | 2023 | 8 | |
| 6 | 2023 | 1 | |
| 7 | 2023 | 13 | |
| 8 | 2023 | 10 | |
| 9 | 2022 | 13 | |
| 10 | 2022 | 4 | |
| 11 | 2022 | 9 | |
| 12 | 2022 | 8 | |
| 13 | 2022 | 24 | |
| 14 | 2021 | 27 | |
| 15 | 2021 | 82 | |
| 16 | 2020 | 50 | |
| 17 | 2019 | 43 | |
| 18 | A Strengthened Dominance Relation Considering Convergence and Diversity for Evolutionary Many-Objective Optimizationbreakdown → | 2018 | 291 |
| 19 | 2018 | 16 | |
| 20 | 2018 | 35 |
About Yansen Su
Yansen Su is a scholar working on Computational Theory and Mathematics, Molecular Biology, Statistical and Nonlinear Physics, Artificial Intelligence and Cancer Research, having authored 106 papers that have together received 2.5k indexed citations. Recurring topics across this work include Gene expression and cancer classification (18 papers), Bioinformatics and Genomic Networks (18 papers), Computational Drug Discovery Methods (14 papers), Single-cell and spatial transcriptomics (13 papers), Gene Regulatory Network Analysis (12 papers), Cancer-related molecular mechanisms research (11 papers), Complex Network Analysis Techniques (10 papers) and MicroRNA in disease regulation (9 papers). The work is most often cited by research in Computational Theory and Mathematics (906 citations), Artificial Intelligence (1.1k citations), Statistical and Nonlinear Physics (262 citations), Information Systems (290 citations) and Molecular Biology (746 citations). Yansen Su has collaborated with scholars based in China, Hong Kong and Japan. Frequent co-authors include Xingyi Zhang, Ye Tian, Yaochu Jin, Chun-Hou Zheng, Xiangxiang Zeng, Lejun Zhang, Ran Cheng, Zilong Jin, Weizheng Wang and Huiling Chen. Their work appears in journals such as Briefings in Bioinformatics, Methods, Frontiers in Genetics, Information Sciences 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.