Andy Liaw
- Ecological Modeling top 0.2%
- Environmental Engineering top 0.2%
- Ecology top 0.2%
- Nature and Landscape Conservation top 0.5%
- Global and Planetary Change top 0.5%
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- Computational Drug Discovery Methods 12
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- Metabolomics and Mass Spectrometry Studies 10
- Protein Structure and Dynamics 2
- Machine Learning in Bioinformatics 2
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- Machine Learning in Materials Science 7
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- Advanced Proteomics Techniques and Applications 4
- Mass Spectrometry Techniques and Applications 3
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- Innovative Microfluidic and Catalytic Techniques Innovation 2
- Co-authors
- Matthew C. WienerRobert P. SheridanVladimir SvetnikLouis R. IversonAnantha PrasadChristopher TongBradley P. FeustonJoseph Culberson
- Journals
- Journal of Chemical Information and Modeling (8 papers)SLAS DISCOVERY (3 papers)Journal of Proteome Research (2 papers)
- Partner nations
- United StatesCanadaNorway
In The Last Decade
Andy Liaw
31 papers receiving 20.6k citations
Hit Papers
Peers
Comparison fields: 5 of 233
- Ecological Modeling 1.3k
- Environmental Engineering 2.7k
- Ecology 4.3k
- Nature and Landscape Conservation 2.0k
- Global and Planetary Change 3.1k
Countries citing papers authored by Andy Liaw
This map shows the geographic impact of Andy Liaw'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 Andy Liaw with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andy Liaw more than expected).
Fields of papers citing papers by Andy Liaw
This network shows the impact of papers produced by Andy Liaw. 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 Andy Liaw. The network helps show where Andy Liaw may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Andy Liaw, 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 | 0 | |
| 2 | 2024 | 3 | |
| 3 | 2023 | 2 | |
| 4 | 2022 | 5 | |
| 5 | 2022 | 10 | |
| 6 | 2020 | 7 | |
| 7 | 2020 | 43 | |
| 8 | 2020 | 34 | |
| 9 | 2019 | 1 | |
| 10 | 2019 | 15 | |
| 11 | 2019 | 9 | |
| 12 | 2017 | 9 | |
| 13 | Extreme Gradient Boosting as a Method for Quantitative Structure–Activity Relationshipsbreakdown → | 2016 | 385 |
| 14 | Deep Neural Nets as a Method for Quantitative Structure–Activity Relationshipsbreakdown → | 2015 | 787 |
| 15 | 2009 | 15 | |
| 16 | 2008 | 8 | |
| 17 | New machine learning tools for predictive vegetation mapping after climate change: Bagging and Random Forest perform better than Regression Tree Analysis. | 2004 | 21 |
| 18 | 2003 | 248 | |
| 19 | 2003 | 50 | |
| 20 | 1994 | 52 |
About Andy Liaw
Andy Liaw is a scholar working on Computational Theory and Mathematics, Ecological Modeling, Physiology, Spectroscopy and Molecular Biology, having authored 32 papers that have together received 21.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (12 papers), Metabolomics and Mass Spectrometry Studies (10 papers), Machine Learning in Materials Science (7 papers), Advanced Proteomics Techniques and Applications (4 papers), Mass Spectrometry Techniques and Applications (3 papers), Innovative Microfluidic and Catalytic Techniques Innovation (2 papers), Protein Structure and Dynamics (2 papers) and Machine Learning in Bioinformatics (2 papers). The work is most often cited by research in Ecological Modeling (1.3k citations), Environmental Engineering (2.7k citations), Ecology (4.3k citations), Nature and Landscape Conservation (2.0k citations) and Global and Planetary Change (3.1k citations). Andy Liaw has collaborated with scholars based in United States, Canada and Norway. Frequent co-authors include Matthew C. Wiener, Robert P. Sheridan, Vladimir Svetnik, Louis R. Iverson, Anantha Prasad, Christopher Tong, Bradley P. Feuston, Joseph Culberson, Junshui Ma and George E. Dahl. Their work appears in journals such as Journal of Chemical Information and Modeling, SLAS DISCOVERY, Journal of Proteome Research, Drug Metabolism and Disposition 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.