Ren Qi
Impact in
- Biophysics top 5%
- Cell Image Analysis Techniques
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- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
Papers in
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- Single-cell and spatial transcriptomics 8
- Gene expression and cancer classification 5
- Bioinformatics and Genomic Networks 2
- Machine Learning in Bioinformatics 2
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- Cancer-related molecular mechanisms research 4
- Co-authors
- Qin Ma (3 shared papers)Quan Zou (5 shared papers)Anjun Ma (3 shared papers)Hongjun Fu (2 shared papers)Cankun Wang (2 shared papers)Yuzhou Chang (1 shared paper)Jianting Gong (1 shared paper)Yuexu Jiang (1 shared paper)
- Journals
- Briefings in Bioinformatics (3 papers)IEEE/ACM Transactions on Computational Biology and Bioinformatics (2 papers)Science China Information Sciences (1 paper)Genome Research (1 paper)Research (1 paper)
- Partner nations
- ChinaUnited StatesSaudi Arabia
In The Last Decade
Ren Qi
14 papers receiving 690 citations
Ren Qi's Hit Papers
Peers
Comparison fields: 5 of 80
- Biophysics 101
- Cancer Research 121
- Molecular Biology 553
- Neurology 48
- Health Informatics 3
Countries citing papers authored by Ren Qi
This map shows the geographic impact of Ren Qi'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 Ren Qi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ren Qi more than expected).
Fields of papers citing papers by Ren Qi
This network shows the impact of papers produced by Ren Qi. 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 Ren Qi. The network helps show where Ren Qi may publish in the future.
Co-authors
The 25 scholars most cited alongside Ren Qi, 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 | scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses Hit paper breakdown → | 2021 | 280 |
| 2 | 2019 | 149 | |
| 3 | 2020 | 75 | |
| 4 | 2020 | 54 | |
| 5 | 2023 | 54 | |
| 6 | 2020 | 41 | |
| 7 | 2022 | 19 | |
| 8 | 2018 | 10 | |
| 9 | 2022 | 6 | |
| 10 | 2025 | 3 | |
| 11 | 2025 | 1 | |
| 12 | Multiple Kernel Geometric Mean Metric Learning for Heterogeneous Data | 2017 | 1 |
| 13 | 2024 | 1 | |
| 14 | 2024 | 1 |
About Ren Qi
Ren Qi is a scholar working on Molecular Biology, Cancer Research, Computer Vision and Pattern Recognition, Artificial Intelligence and Immunology, having authored 14 papers that have together received 695 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (8 papers), Gene expression and cancer classification (5 papers), Cancer-related molecular mechanisms research (4 papers), Face and Expression Recognition (3 papers), Immune cells in cancer (2 papers), Bioinformatics and Genomic Networks (2 papers), Machine Learning in Bioinformatics (2 papers) and Machine Learning and ELM (1 paper). The work is most often cited by research in Biophysics (101 citations), Cancer Research (121 citations), Molecular Biology (553 citations), Neurology (48 citations) and Health Informatics (3 citations). Ren Qi has collaborated with scholars based in China, United States and Saudi Arabia. Frequent co-authors include Qin Ma, Quan Zou, Anjun Ma, Hongjun Fu, Cankun Wang, Yuzhou Chang, Jianting Gong, Yuexu Jiang, Juexin Wang and Dong Xu. Their work appears in journals such as Briefings in Bioinformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Science China Information Sciences, Genome Research and Research.
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.