Ning Tu
Impact in
- Modeling and Simulation top 10%
-
- Cancer-related Molecular Pathways
Papers in
-
- COVID-19 and Mental Health 3
-
- Functional Brain Connectivity Studies 5
- Co-authors
- Guangyao Wu (5 shared papers)J Y Ro (1 shared paper)Waun Ki Hong (1 shared paper)Zhi Wen (3 shared papers)Walter N. Hittelman (1 shared paper)Lihong Bu (14 shared papers)Peng Tang (1 shared paper)Ke Wang (1 shared paper)
- Journals
- Frontiers in Psychiatry (3 papers)Journal of Clinical Oncology (1 paper)Medicine (1 paper)Neural Plasticity (1 paper)Current Microbiology (1 paper)
- Partner nations
- ChinaUnited StatesSpain
In The Last Decade
Ning Tu
25 papers receiving 481 citations
Peers
Comparison fields: 5 of 89
- Modeling and Simulation 18
- Oncology 91
- Pulmonary and Respiratory Medicine 93
- Cancer Research 42
- Virology 12
Countries citing papers authored by Ning Tu
This map shows the geographic impact of Ning Tu'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 Ning Tu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ning Tu more than expected).
Fields of papers citing papers by Ning Tu
This network shows the impact of papers produced by Ning Tu. 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 Ning Tu. The network helps show where Ning Tu may publish in the future.
Co-authors
The 25 scholars most cited alongside Ning Tu, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1995 | 133 | |
| 2 | 2017 | 69 | |
| 3 | 2020 | 58 | |
| 4 | 2018 | 24 | |
| 5 | 2018 | 24 | |
| 6 | 2022 | 22 | |
| 7 | 2021 | 21 | |
| 8 | 2021 | 16 | |
| 9 | 2022 | 15 | |
| 10 | 2022 | 15 | |
| 11 | 2022 | 14 | |
| 12 | 2017 | 13 | |
| 13 | 2021 | 11 | |
| 14 | 2020 | 7 | |
| 15 | 2020 | 7 | |
| 16 | 2019 | 7 | |
| 17 | 2024 | 6 | |
| 18 | 2020 | 6 | |
| 19 | 2023 | 5 | |
| 20 | 2024 | 5 |
About Ning Tu
Ning Tu is a scholar working on Clinical Psychology, Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging, Neurology and Pulmonary and Respiratory Medicine, having authored 26 papers that have together received 489 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (5 papers), Advanced Neuroimaging Techniques and Applications (4 papers), COVID-19 and Mental Health (3 papers), MRI in cancer diagnosis (2 papers), COVID-19 epidemiological studies (2 papers), Long-Term Effects of COVID-19 (2 papers), Sarcoma Diagnosis and Treatment (1 paper) and Neurofibromatosis and Schwannoma Cases (1 paper). The work is most often cited by research in Modeling and Simulation (18 citations), Oncology (91 citations), Pulmonary and Respiratory Medicine (93 citations), Cancer Research (42 citations) and Virology (12 citations). Ning Tu has collaborated with scholars based in China, United States and Spain. Frequent co-authors include Guangyao Wu, J Y Ro, Waun Ki Hong, Zhi Wen, Walter N. Hittelman, Lihong Bu, Peng Tang, Ke Wang, Jie Zhang and Hongyan Feng. Their work appears in journals such as Frontiers in Psychiatry, Journal of Clinical Oncology, Medicine, Neural Plasticity and Current Microbiology.
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.