Shida Zhu
Impact in
- Cancer Research top 10%
- Cancer Genomics and Diagnostics
- Cancer-related molecular mechanisms research
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- Single-cell and spatial transcriptomics
- CRISPR and Genetic Engineering
- Epigenetics and DNA Methylation
- RNA modifications and cancer
Papers in
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- DNA Repair Mechanisms 4
- Gut microbiota and health 4
- CRISPR and Genetic Engineering 3
- Oncology 13
- PARP inhibition in cancer therapy 4
- Cancer Cells and Metastasis 3
- Co-authors
- Huanming Yang (8 shared papers)Xun Xu (6 shared papers)Longqi Liu (2 shared papers)Zhouchun Shang (2 shared papers)Dongbing Liu (3 shared papers)Chuanyu Liu (2 shared papers)Liang Wu (2 shared papers)Hongmei Zhu (2 shared papers)
In The Last Decade
Shida Zhu
31 papers receiving 480 citations
Peers
Comparison fields: 5 of 76
- Cancer Research 162
- Molecular Biology 276
- Oncology 99
- Pathology and Forensic Medicine 49
- Hepatology 20
Countries citing papers authored by Shida Zhu
This map shows the geographic impact of Shida Zhu'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 Shida Zhu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shida Zhu more than expected).
Fields of papers citing papers by Shida Zhu
This network shows the impact of papers produced by Shida Zhu. 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 Shida Zhu. The network helps show where Shida Zhu may publish in the future.
Co-authors
The 25 scholars most cited alongside Shida Zhu, 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 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 82 | |
| 2 | 2018 | 70 | |
| 3 | 2018 | 40 | |
| 4 | 2016 | 30 | |
| 5 | 2014 | 26 | |
| 6 | 2020 | 24 | |
| 7 | 2022 | 24 | |
| 8 | 2021 | 20 | |
| 9 | 2021 | 20 | |
| 10 | 2024 | 18 | |
| 11 | 2023 | 17 | |
| 12 | 2022 | 17 | |
| 13 | 2016 | 17 | |
| 14 | 2015 | 12 | |
| 15 | 2023 | 11 | |
| 16 | 2024 | 9 | |
| 17 | 2020 | 8 | |
| 18 | 2018 | 7 | |
| 19 | 2019 | 5 | |
| 20 | 2024 | 5 |
About Shida Zhu
Shida Zhu is a scholar working on Molecular Biology, Oncology, Cancer Research, Pathology and Forensic Medicine and Genetics, having authored 37 papers that have together received 484 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (8 papers), DNA Repair Mechanisms (4 papers), PARP inhibition in cancer therapy (4 papers), Gut microbiota and health (4 papers), Genetic factors in colorectal cancer (3 papers), Cancer Cells and Metastasis (3 papers), BRCA gene mutations in cancer (3 papers) and CRISPR and Genetic Engineering (3 papers). The work is most often cited by research in Cancer Research (162 citations), Molecular Biology (276 citations), Oncology (99 citations), Pathology and Forensic Medicine (49 citations) and Hepatology (20 citations). Shida Zhu has collaborated with scholars based in China, Denmark and Hong Kong. Frequent co-authors include Huanming Yang, Xun Xu, Longqi Liu, Zhouchun Shang, Dongbing Liu, Chuanyu Liu, Liang Wu, Hongmei Zhu, Jian Wang and Yijun Song. Their work appears in journals such as Nature Communications, Scientific Reports, Annals of Oncology, BMC Genomics and PLoS ONE.
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.