Bowei Yan
Impact in
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- Computational Drug Discovery Methods
- Topological and Geometric Data Analysis
Papers in
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- Computational Drug Discovery Methods 5
-
- Bioinformatics and Genomic Networks 3
- Single-cell and spatial transcriptomics 1
- Co-authors
- Lianlian Wu (9 shared papers)Song He (10 shared papers)Xiaochen Bo (7 shared papers)Yuqi Wen (6 shared papers)Dongjin Leng (3 shared papers)Qianqian Xu (1 shared paper)Yixin Zhang (2 shared papers)Weisi Lin (1 shared paper)
- Journals
- Briefings in Bioinformatics (3 papers)Nucleic Acids Research (1 paper)Expert Systems with Applications (1 paper)BMC Bioinformatics (1 paper)International Journal of Applied Earth Observation and Geoinformation (1 paper)
- Partner nations
- ChinaUnited StatesSweden
In The Last Decade
Bowei Yan
15 papers receiving 361 citations
Peers
Comparison fields: 5 of 39
- Computational Theory and Mathematics 146
- Health Informatics 3
- Computer Vision and Pattern Recognition 35
- Computer Science Applications 7
- Aging 1
Countries citing papers authored by Bowei Yan
This map shows the geographic impact of Bowei 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 Bowei Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bowei Yan more than expected).
Fields of papers citing papers by Bowei Yan
This network shows the impact of papers produced by Bowei 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 Bowei Yan. The network helps show where Bowei Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside Bowei 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
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 91 | |
| 2 | 2022 | 65 | |
| 3 | 2012 | 63 | |
| 4 | 2021 | 32 | |
| 5 | 2022 | 32 | |
| 6 | 2021 | 22 | |
| 7 | 2016 | 15 | |
| 8 | Convergence of Gradient EM on Multi-component Mixture of Gaussians | 2017 | 14 |
| 9 | 2022 | 12 | |
| 10 | 2021 | 6 | |
| 11 | 2023 | 4 | |
| 12 | 2025 | 4 | |
| 13 | 2022 | 3 | |
| 14 | 2021 | 2 | |
| 15 | 2025 | 2 |
About Bowei Yan
Bowei Yan is a scholar working on Computational Theory and Mathematics, Molecular Biology, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 15 papers that have together received 367 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (5 papers), Bioinformatics and Genomic Networks (3 papers), Complex Network Analysis Techniques (1 paper), Bayesian Methods and Mixture Models (1 paper), Image and Video Quality Assessment (1 paper) and Single-cell and spatial transcriptomics (1 paper). The work is most often cited by research in Computational Theory and Mathematics (146 citations), Health Informatics (3 citations), Computer Vision and Pattern Recognition (35 citations), Computer Science Applications (7 citations) and Aging (1 citation). Bowei Yan has collaborated with scholars based in China, United States and Sweden. Frequent co-authors include Lianlian Wu, Song He, Xiaochen Bo, Yuqi Wen, Dongjin Leng, Qianqian Xu, Yixin Zhang, Weisi Lin, Tingting Jiang and Yuan Yao. Their work appears in journals such as Briefings in Bioinformatics, Nucleic Acids Research, Expert Systems with Applications, BMC Bioinformatics and International Journal of Applied Earth Observation and Geoinformation.
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.