Lieyang Chen
Impact in
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- Computational Drug Discovery Methods
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- Protein Structure and Dynamics
- Bioinformatics and Genomic Networks
- Genetics, Bioinformatics, and Biomedical Research
- vaccines and immunoinformatics approaches
Papers in
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- Protein Structure and Dynamics 5
- Cell death mechanisms and regulation 1
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- Computational Drug Discovery Methods 4
- Co-authors
- Tom Kurtzman (4 shared papers)Anthony Cruz (3 shared papers)Steven Ramsey (1 shared paper)Callum J. Dickson (1 shared paper)David Ryan Koes (1 shared paper)José S. Duca (1 shared paper)Viktor Horn̆ák (1 shared paper)Jinfa Gu (1 shared paper)
- Journals
- Physical Chemistry Chemical Physics (1 paper)Human Cell (1 paper)Journal of Chemical Information and Modeling (1 paper)PLoS ONE (1 paper)Journal of Computer-Aided Molecular Design (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Lieyang Chen
6 papers receiving 237 citations
Peers
Comparison fields: 5 of 63
- Computational Theory and Mathematics 168
- Molecular Biology 177
- Materials Chemistry 90
- Pharmacology 27
- Biophysics 7
Countries citing papers authored by Lieyang Chen
This map shows the geographic impact of Lieyang Chen'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 Lieyang Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lieyang Chen more than expected).
Fields of papers citing papers by Lieyang Chen
This network shows the impact of papers produced by Lieyang Chen. 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 Lieyang Chen. The network helps show where Lieyang Chen may publish in the future.
Co-authors
The 21 scholars most cited alongside Lieyang Chen, 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 | 2019 | 169 | |
| 2 | 2021 | 25 | |
| 3 | 2014 | 23 | |
| 4 | 2023 | 12 | |
| 5 | 2020 | 8 | |
| 6 | 2022 | 5 |
About Lieyang Chen
Lieyang Chen is a scholar working on Molecular Biology, Computational Theory and Mathematics, Physical and Theoretical Chemistry, Materials Chemistry and Statistical and Nonlinear Physics, having authored 6 papers that have together received 242 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (5 papers), Computational Drug Discovery Methods (4 papers), Machine Learning in Materials Science (2 papers), interferon and immune responses (1 paper), Cell death mechanisms and regulation (1 paper), Crystallography and molecular interactions (1 paper), Advanced Thermodynamics and Statistical Mechanics (1 paper) and Spectroscopy and Quantum Chemical Studies (1 paper). The work is most often cited by research in Computational Theory and Mathematics (168 citations), Molecular Biology (177 citations), Materials Chemistry (90 citations), Pharmacology (27 citations) and Biophysics (7 citations). Lieyang Chen has collaborated with scholars based in United States and China. Frequent co-authors include Tom Kurtzman, Anthony Cruz, Steven Ramsey, Callum J. Dickson, David Ryan Koes, José S. Duca, Viktor Horn̆ák, Jinfa Gu, Qiang Pan‐Hammarström and Lauren Wickstrom. Their work appears in journals such as Physical Chemistry Chemical Physics, Human Cell, Journal of Chemical Information and Modeling, PLoS ONE and Journal of Computer-Aided Molecular Design.
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.