Ting Gui
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Molecular Biology top 5%
- DNA Repair Mechanisms
- Extracellular vesicles in disease
- RNA modifications and cancer
- CRISPR and Genetic Engineering
Papers in
-
- TGF-β signaling in diseases 4
- Renal and related cancers 3
- Circular RNAs in diseases 3
- Oncology 11
- Drug Transport and Resistance Mechanisms 5
- Cancer Cells and Metastasis 3
- Co-authors
- Zhibo Gai (23 shared papers)Yasuteru Muragaki (12 shared papers)Yujing Sun (8 shared papers)Aiko Shimokado (7 shared papers)Xialu Li (2 shared papers)Gerd A. Kullak‐Ublick (9 shared papers)Jie Liu (1 shared paper)Wenjian Gan (1 shared paper)
- Journals
- PLoS ONE (4 papers)Experimental and Molecular Pathology (3 papers)OncoTargets and Therapy (3 papers)BioMed Research International (2 papers)Journal of Biological Chemistry (2 papers)
- Partner nations
- ChinaSwitzerlandJapan
In The Last Decade
Ting Gui
55 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 124
- Cancer Research 387
- Molecular Biology 1.3k
- Reproductive Medicine 115
- Nephrology 91
- Oncology 307
Countries citing papers authored by Ting Gui
This map shows the geographic impact of Ting Gui'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 Ting Gui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ting Gui more than expected).
Fields of papers citing papers by Ting Gui
This network shows the impact of papers produced by Ting Gui. 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 Ting Gui. The network helps show where Ting Gui may publish in the future.
Co-authors
The 25 scholars most cited alongside Ting Gui, 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 58 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 361 | |
| 2 | 2013 | 265 | |
| 3 | 2012 | 166 | |
| 4 | 2020 | 143 | |
| 5 | 2012 | 124 | |
| 6 | 2021 | 103 | |
| 7 | 2012 | 95 | |
| 8 | 2018 | 83 | |
| 9 | 2015 | 82 | |
| 10 | 2015 | 77 | |
| 11 | 2012 | 69 | |
| 12 | 2021 | 61 | |
| 13 | 2010 | 53 | |
| 14 | 2009 | 52 | |
| 15 | 2014 | 46 | |
| 16 | 2015 | 43 | |
| 17 | 2011 | 43 | |
| 18 | 2010 | 38 | |
| 19 | 2020 | 37 | |
| 20 | 2019 | 35 |
About Ting Gui
Ting Gui is a scholar working on Molecular Biology, Oncology, Cancer Research, Epidemiology and Surgery, having authored 58 papers that have together received 2.5k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (5 papers), Liver Disease Diagnosis and Treatment (5 papers), Drug Transport and Resistance Mechanisms (5 papers), MicroRNA in disease regulation (5 papers), TGF-β signaling in diseases (4 papers), Renal and related cancers (3 papers), Cancer Cells and Metastasis (3 papers) and Circular RNAs in diseases (3 papers). The work is most often cited by research in Cancer Research (387 citations), Molecular Biology (1.3k citations), Reproductive Medicine (115 citations), Nephrology (91 citations) and Oncology (307 citations). Ting Gui has collaborated with scholars based in China, Switzerland and Japan. Frequent co-authors include Zhibo Gai, Yasuteru Muragaki, Yujing Sun, Aiko Shimokado, Xialu Li, Gerd A. Kullak‐Ublick, Jie Liu, Wenjian Gan, James L. Manley and Keng Shen. Their work appears in journals such as PLoS ONE, Experimental and Molecular Pathology, OncoTargets and Therapy, BioMed Research International and Journal of Biological Chemistry.
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.