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
Papers in
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- Computational Drug Discovery Methods 4
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- thermodynamics and calorimetric analyses 1
- Co-authors
- Tom Kurtzman (4 shared papers)Anthony Cruz (3 shared papers)David Ryan Koes (1 shared paper)Viktor Horn̆ák (1 shared paper)Steven Ramsey (1 shared paper)Callum J. Dickson (1 shared paper)José S. Duca (1 shared paper)Lauren Wickstrom (2 shared papers)
- Journals
- Journal of Chemical Theory and Computation (1 paper)Journal of Chemical Information and Modeling (1 paper)Journal of Computer-Aided Molecular Design (1 paper)Human Cell (1 paper)Physical Chemistry Chemical Physics (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Lieyang Chen
6 papers receiving 263 citations
Peers
Comparison fields: 5 of 63
- Computational Theory and Mathematics 183
- Molecular Biology 176
- Materials Chemistry 92
- Pharmacology 28
- Health Informatics 2
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 | 190 | |
| 2 | 2021 | 27 | |
| 3 | 2014 | 24 | |
| 4 | 2023 | 14 | |
| 5 | 2020 | 10 | |
| 6 | 2022 | 5 |
About Lieyang Chen
Lieyang Chen is a scholar working on Computational Theory and Mathematics, Physical and Theoretical Chemistry, Molecular Biology, Statistical and Nonlinear Physics and Materials Chemistry, having authored 6 papers that have together received 270 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), Advanced Thermodynamics and Statistical Mechanics (1 paper), thermodynamics and calorimetric analyses (1 paper), Spectroscopy and Quantum Chemical Studies (1 paper) and Virus-based gene therapy research (1 paper). The work is most often cited by research in Computational Theory and Mathematics (183 citations), Molecular Biology (176 citations), Materials Chemistry (92 citations), Pharmacology (28 citations) and Health Informatics (2 citations). Lieyang Chen has collaborated with scholars based in United States and China. Frequent co-authors include Tom Kurtzman, Anthony Cruz, David Ryan Koes, Viktor Horn̆ák, Steven Ramsey, Callum J. Dickson, José S. Duca, Lauren Wickstrom, Jinfa Gu and Qiang Pan‐Hammarström. Their work appears in journals such as Journal of Chemical Theory and Computation, Journal of Chemical Information and Modeling, Journal of Computer-Aided Molecular Design, Human Cell and Physical Chemistry Chemical Physics.
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.