Lu Tan
Impact in
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- Computational Drug Discovery Methods
- Pharmacology top 5%
- Pharmacogenetics and Drug Metabolism
- Microbial Natural Products and Biosynthesis
Papers in
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- Computational Drug Discovery Methods 13
-
- Protein Structure and Dynamics 4
- Metabolomics and Mass Spectrometry Studies 2
- Co-authors
- Jürgen Bajorath (8 shared papers)Johannes Kirchmair (5 shared papers)Robert C. Glen (3 shared papers)Jonathan D. Tyzack (1 shared paper)Andreas Bender (1 shared paper)Mark J. Williamson (1 shared paper)Peter J. Bond (1 shared paper)Stefan J. Marciniak (4 shared papers)
- Journals
- Journal of Chemical Information and Modeling (4 papers)Current Pharmaceutical Design (2 papers)Journal of Hepatology (1 paper)Hepatology (1 paper)The FASEB Journal (1 paper)
- Partner nations
- United KingdomGermanySwitzerland
In The Last Decade
Lu Tan
22 papers receiving 687 citations
Peers
Comparison fields: 5 of 90
- Computational Theory and Mathematics 282
- Pharmacology 119
- Cancer Research 96
- Cell Biology 102
- Molecular Biology 392
Countries citing papers authored by Lu Tan
This map shows the geographic impact of Lu Tan'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 Lu Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lu Tan more than expected).
Fields of papers citing papers by Lu Tan
This network shows the impact of papers produced by Lu Tan. 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 Lu Tan. The network helps show where Lu Tan may publish in the future.
Co-authors
The 25 scholars most cited alongside Lu Tan, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 221 | |
| 2 | 2012 | 93 | |
| 3 | 2008 | 59 | |
| 4 | 2018 | 45 | |
| 5 | 2015 | 39 | |
| 6 | 2007 | 36 | |
| 7 | 2008 | 31 | |
| 8 | 2017 | 30 | |
| 9 | 2012 | 24 | |
| 10 | 2014 | 23 | |
| 11 | 2010 | 21 | |
| 12 | 2020 | 21 | |
| 13 | 2024 | 16 | |
| 14 | 2009 | 14 | |
| 15 | 2009 | 13 | |
| 16 | 2009 | 11 | |
| 17 | 2013 | 4 | |
| 18 | 2010 | 3 | |
| 19 | 2012 | 2 | |
| 20 | 2023 | 2 |
About Lu Tan
Lu Tan is a scholar working on Computational Theory and Mathematics, Molecular Biology, Pharmacology, Cell Biology and Cancer Research, having authored 22 papers that have together received 710 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (13 papers), Protein Structure and Dynamics (4 papers), Microbial Natural Products and Biosynthesis (4 papers), Endoplasmic Reticulum Stress and Disease (3 papers), High Altitude and Hypoxia (2 papers), HIV/AIDS drug development and treatment (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers) and Protease and Inhibitor Mechanisms (2 papers). The work is most often cited by research in Computational Theory and Mathematics (282 citations), Pharmacology (119 citations), Cancer Research (96 citations), Cell Biology (102 citations) and Molecular Biology (392 citations). Lu Tan has collaborated with scholars based in United Kingdom, Germany and Switzerland. Frequent co-authors include Jürgen Bajorath, Johannes Kirchmair, Robert C. Glen, Jonathan D. Tyzack, Andreas Bender, Mark J. Williamson, Peter J. Bond, Stefan J. Marciniak, David A. Lomas and A. Ordóñez. Their work appears in journals such as Journal of Chemical Information and Modeling, Current Pharmaceutical Design, Journal of Hepatology, Hepatology and The FASEB Journal.
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.