Tao Che
Impact in
-
- Neuropeptides and Animal Physiology
- Neurotransmitter Receptor Influence on Behavior
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
Papers in
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- Neuropeptides and Animal Physiology 25
-
- Antibiotic Resistance in Bacteria 5
- Co-authors
- Bryan L. RothBrian K. ShoichetAnat LevitDaniel WackerSheng WangJohn D. McCorvyJeffrey F. DiBertoJiankun Lyu
- Journals
- Nature (6 papers)Biochemistry (6 papers)Nature Communications (4 papers)Nature Chemical Biology (4 papers)ACS Chemical Neuroscience (3 papers)
- Partner nations
- United StatesChinaGermany
In The Last Decade
Tao Che
67 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 148
- Cellular and Molecular Neuroscience 1.2k
- Computational Theory and Mathematics 751
- Molecular Biology 2.3k
- Pharmacology 155
- Pharmacology 293
Countries citing papers authored by Tao Che
This map shows the geographic impact of Tao Che'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 Tao Che with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tao Che more than expected).
Fields of papers citing papers by Tao Che
This network shows the impact of papers produced by Tao Che. 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 Tao Che. The network helps show where Tao Che may publish in the future.
Co-authors
The 25 scholars most cited alongside Tao Che, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 3 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 1 | |
| 5 | 2024 | 36 | |
| 6 | 2024 | 22 | |
| 7 | 2024 | 18 | |
| 8 | 2024 | 1 | |
| 9 | 2023 | 6 | |
| 10 | 2023 | 19 | |
| 11 | 2023 | 43 | |
| 12 | 2022 | 72 | |
| 13 | 2022 | 77 | |
| 14 | Structure of a Hallucinogen-Activated Gq-Coupled 5-HT2A Serotonin Receptor Hit paper breakdown → | 2020 | 306 |
| 15 | 2020 | 93 | |
| 16 | 2018 | 116 | |
| 17 | Structure of the D2 dopamine receptor bound to the atypical antipsychotic drug risperidone Hit paper breakdown → | 2018 | 331 |
| 18 | 2017 | 17 | |
| 19 | 2017 | 217 | |
| 20 | 2016 | 34 |
About Tao Che
Tao Che is a scholar working on Cellular and Molecular Neuroscience, Molecular Medicine, Pharmacology, Molecular Biology and Biophysics, having authored 69 papers that have together received 3.5k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (33 papers), Neuropeptides and Animal Physiology (25 papers), Pharmacological Receptor Mechanisms and Effects (16 papers), Monoclonal and Polyclonal Antibodies Research (6 papers), Chemical synthesis and alkaloids (5 papers), Antibiotic Resistance in Bacteria (5 papers), Perovskite Materials and Applications (4 papers) and Computational Drug Discovery Methods (4 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (1.2k citations), Computational Theory and Mathematics (751 citations), Molecular Biology (2.3k citations), Pharmacology (155 citations) and Pharmacology (293 citations). Tao Che has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Bryan L. Roth, Brian K. Shoichet, Anat Levit, Daniel Wacker, Sheng Wang, John D. McCorvy, Jeffrey F. DiBerto, Jiankun Lyu, B. Krumm and Yurii S. Moroz. Their work appears in journals such as Nature, Biochemistry, Nature Communications, Nature Chemical Biology and ACS Chemical Neuroscience.
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.