Bowei Yan
Impact in
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- Computational Drug Discovery Methods
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- Pharmacogenetics and Drug Metabolism
Papers in
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- Bioinformatics and Genomic Networks 5
- Metabolomics and Mass Spectrometry Studies 4
- Gene expression and cancer classification 3
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- Computational Drug Discovery Methods 6
- Co-authors
- Lianlian Wu (9 shared papers)Song He (10 shared papers)Xiaochen Bo (8 shared papers)Yuqi Wen (6 shared papers)Chong Dai (3 shared papers)Dongjin Leng (3 shared papers)Yixin Zhang (2 shared papers)Weisi Lin (1 shared paper)
- Journals
- Briefings in Bioinformatics (3 papers)BMC Bioinformatics (1 paper)Molecules (1 paper)Expert Systems with Applications (1 paper)IEEE Transactions on Multimedia (1 paper)
- Partner nations
- ChinaUnited StatesSweden
In The Last Decade
Bowei Yan
18 papers receiving 322 citations
Peers
Comparison fields: 5 of 91
- Computational Theory and Mathematics 147
- Pharmacology 21
- Biophysics 13
- Molecular Biology 153
- Computer Science Applications 11
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 | 77 | |
| 2 | 2022 | 53 | |
| 3 | 2012 | 51 | |
| 4 | 2021 | 30 | |
| 5 | 2022 | 29 | |
| 6 | 2021 | 18 | |
| 7 | 2016 | 15 | |
| 8 | Convergence of Gradient EM on Multi-component Mixture of Gaussians | 2017 | 12 |
| 9 | 2023 | 12 | |
| 10 | 2022 | 9 | |
| 11 | On Robustness of Kernel Clustering | 2016 | 5 |
| 12 | 2021 | 5 | |
| 13 | 2022 | 3 | |
| 14 | 2023 | 3 | |
| 15 | 2025 | 2 | |
| 16 | Exact Recovery of Number of Blocks in Blockmodels | 2017 | 2 |
| 17 | 2025 | 1 | |
| 18 | 2021 | 1 | |
| 19 | Statistical Convergence Analysis of Gradient EM on General Gaussian Mixture Models | 2017 | 0 |
| 20 | 2023 | 0 |
About Bowei Yan
Bowei Yan is a scholar working on Molecular Biology, Computational Theory and Mathematics, Artificial Intelligence, Pharmacology and Statistics and Probability, having authored 20 papers that have together received 328 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Bioinformatics and Genomic Networks (5 papers), Metabolomics and Mass Spectrometry Studies (4 papers), Statistical Methods and Inference (3 papers), Gene expression and cancer classification (3 papers), Pharmacogenetics and Drug Metabolism (2 papers), Markov Chains and Monte Carlo Methods (2 papers) and Bayesian Methods and Mixture Models (2 papers). The work is most often cited by research in Computational Theory and Mathematics (147 citations), Pharmacology (21 citations), Biophysics (13 citations), Molecular Biology (153 citations) and Computer Science Applications (11 citations). 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, Chong Dai, Dongjin Leng, Yixin Zhang, Weisi Lin, Qingming Huang and Yuan Yao. Their work appears in journals such as Briefings in Bioinformatics, BMC Bioinformatics, Molecules, Expert Systems with Applications and IEEE Transactions on Multimedia.
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.