Pei-Chi Tu
Impact in
- Biological Psychiatry top 0.5%
- Tryptophan and brain disorders
- Neurology top 2%
- Transcranial Magnetic Stimulation Studies
Papers in
-
- Functional Brain Connectivity Studies 16
- Neural dynamics and brain function 4
- Pharmacology 15
- Treatment of Major Depression 15
- Co-authors
- Tung‐Ping Su (47 shared papers)Cheng‐Ta Li (46 shared papers)Mu‐Hong Chen (41 shared papers)Ya‐Mei Bai (38 shared papers)Shih‐Jen Tsai (30 shared papers)Jen‐Chuen Hsieh (11 shared papers)Chen-Jee Hong (20 shared papers)Chih‐Ming Cheng (12 shared papers)
- Journals
- Journal of Affective Disorders (10 papers)PLoS ONE (5 papers)CNS Spectrums (3 papers)Psychiatry Research (3 papers)Scientific Reports (3 papers)
- Partner nations
- TaiwanUnited StatesFinland
In The Last Decade
Pei-Chi Tu
58 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 90
- Biological Psychiatry 542
- Neurology 392
- Behavioral Neuroscience 167
- Cognitive Neuroscience 706
- Pharmacology 561
Countries citing papers authored by Pei-Chi Tu
This map shows the geographic impact of Pei-Chi 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 Pei-Chi Tu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pei-Chi Tu more than expected).
Fields of papers citing papers by Pei-Chi Tu
This network shows the impact of papers produced by Pei-Chi 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 Pei-Chi Tu. The network helps show where Pei-Chi Tu may publish in the future.
Co-authors
The 25 scholars most cited alongside Pei-Chi 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 60 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 222 | |
| 2 | 2017 | 171 | |
| 3 | 2012 | 153 | |
| 4 | 2014 | 120 | |
| 5 | 2018 | 117 | |
| 6 | 2011 | 111 | |
| 7 | 2019 | 82 | |
| 8 | 2012 | 77 | |
| 9 | 2015 | 67 | |
| 10 | 2020 | 67 | |
| 11 | 2018 | 65 | |
| 12 | 2019 | 65 | |
| 13 | 2019 | 65 | |
| 14 | 2018 | 56 | |
| 15 | 2020 | 52 | |
| 16 | 2017 | 50 | |
| 17 | 2014 | 49 | |
| 18 | 2012 | 48 | |
| 19 | 2019 | 46 | |
| 20 | 2014 | 43 |
About Pei-Chi Tu
Pei-Chi Tu is a scholar working on Cognitive Neuroscience, Pharmacology, Psychiatry and Mental health, Biological Psychiatry and Experimental and Cognitive Psychology, having authored 60 papers that have together received 2.3k indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (16 papers), Treatment of Major Depression (15 papers), Bipolar Disorder and Treatment (11 papers), Tryptophan and brain disorders (9 papers), Transcranial Magnetic Stimulation Studies (5 papers), Advanced Neuroimaging Techniques and Applications (4 papers), Neural dynamics and brain function (4 papers) and Mental Health Research Topics (3 papers). The work is most often cited by research in Biological Psychiatry (542 citations), Neurology (392 citations), Behavioral Neuroscience (167 citations), Cognitive Neuroscience (706 citations) and Pharmacology (561 citations). Pei-Chi Tu has collaborated with scholars based in Taiwan, United States and Finland. Frequent co-authors include Tung‐Ping Su, Cheng‐Ta Li, Mu‐Hong Chen, Ya‐Mei Bai, Shih‐Jen Tsai, Jen‐Chuen Hsieh, Chen-Jee Hong, Chih‐Ming Cheng, Li‐Fen Chen and Ying-Chiao Lee. Their work appears in journals such as Journal of Affective Disorders, PLoS ONE, CNS Spectrums, Psychiatry Research and Scientific Reports.
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.