Qingxia Yang
Impact in
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- Computational Drug Discovery Methods
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
Papers in
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- Metabolomics and Mass Spectrometry Studies 16
- Bioinformatics and Genomic Networks 16
- Gene expression and cancer classification 14
- Single-cell and spatial transcriptomics 4
- Spectroscopy 12
- Advanced Proteomics Techniques and Applications 12
- Co-authors
- Feng Zhu (24 shared papers)Jing Tang (18 shared papers)Weiwei Xue (15 shared papers)Xuejiao Cui (8 shared papers)Bo Li (15 shared papers)Yu Chen (8 shared papers)Yunxia Wang (12 shared papers)Yinghong Li (7 shared papers)
In The Last Decade
Qingxia Yang
55 papers receiving 2.8k citations
Qingxia Yang's Hit Papers
Peers
Comparison fields: 5 of 164
- Computational Theory and Mathematics 496
- Cancer Research 430
- Molecular Biology 1.9k
- Pharmacology 163
- Spectroscopy 268
Countries citing papers authored by Qingxia Yang
This map shows the geographic impact of Qingxia Yang'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 Qingxia Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingxia Yang more than expected).
Fields of papers citing papers by Qingxia Yang
This network shows the impact of papers produced by Qingxia Yang. 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 Qingxia Yang. The network helps show where Qingxia Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Qingxia Yang, 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 59 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Therapeutic target database update 2018: enriched resource for facilitating bench-to-clinic research of targeted therapeutics Hit paper breakdown → | 2017 | 418 |
| 2 | 2017 | 302 | |
| 3 | 2019 | 207 | |
| 4 | 2018 | 162 | |
| 5 | 2020 | 162 | |
| 6 | 2021 | 149 | |
| 7 | 2021 | 134 | |
| 8 | 2016 | 119 | |
| 9 | 2019 | 101 | |
| 10 | 2020 | 99 | |
| 11 | 2023 | 84 | |
| 12 | 2018 | 77 | |
| 13 | 2018 | 69 | |
| 14 | 2020 | 60 | |
| 15 | 2022 | 59 | |
| 16 | 2019 | 50 | |
| 17 | 2022 | 44 | |
| 18 | 2022 | 36 | |
| 19 | 2019 | 34 | |
| 20 | 2019 | 33 |
About Qingxia Yang
Qingxia Yang is a scholar working on Molecular Biology, Spectroscopy, Cancer Research, Genetics and Computational Theory and Mathematics, having authored 59 papers that have together received 2.8k indexed citations. Recurring topics across this work include Metabolomics and Mass Spectrometry Studies (16 papers), Bioinformatics and Genomic Networks (16 papers), Gene expression and cancer classification (14 papers), Advanced Proteomics Techniques and Applications (12 papers), Genetic Associations and Epidemiology (4 papers), Single-cell and spatial transcriptomics (4 papers), Computational Drug Discovery Methods (4 papers) and Cancer Genomics and Diagnostics (3 papers). The work is most often cited by research in Computational Theory and Mathematics (496 citations), Cancer Research (430 citations), Molecular Biology (1.9k citations), Pharmacology (163 citations) and Spectroscopy (268 citations). Qingxia Yang has collaborated with scholars based in China, Singapore and Macao. Frequent co-authors include Feng Zhu, Jing Tang, Weiwei Xue, Xuejiao Cui, Bo Li, Yu Chen, Yunxia Wang, Yinghong Li, Yunqing Qiu and Jianbo Fu. Their work appears in journals such as Briefings in Bioinformatics, Nucleic Acids Research, Analytical Chemistry, Frontiers in Pharmacology and The Science of The Total Environment.
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.