Andy Liaw

28.3k total citations · 5 hit papers
32 papers, 21.2k citations indexed

About

Andy Liaw is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Andy Liaw has authored 32 papers receiving a total of 21.2k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 12 papers in Computational Theory and Mathematics and 7 papers in Materials Chemistry. Recurrent topics in Andy Liaw's work include Computational Drug Discovery Methods (12 papers), Metabolomics and Mass Spectrometry Studies (10 papers) and Machine Learning in Materials Science (7 papers). Andy Liaw is often cited by papers focused on Computational Drug Discovery Methods (12 papers), Metabolomics and Mass Spectrometry Studies (10 papers) and Machine Learning in Materials Science (7 papers). Andy Liaw collaborates with scholars based in United States, Canada and Norway. Andy Liaw's 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 and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Scientific Reports and Journal of Medicinal Chemistry.

In The Last Decade

Andy Liaw

31 papers receiving 20.6k citations

Hit Papers

Classification and Regression by randomForest 2003 2026 2010 2018 2007 2003 2006 2015 2016 4.0k 8.0k 12.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Classification and Regression by randomForest
    2007 14.4k citations Andy Liaw et al. profile →
  2. Random Forest:  A Classification and Regression Tool for Compound Classification and QSAR Modeling
    2003 2.6k citations Vladimir Svetnik, Andy Liaw et al. profile →
  3. Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction
    2006 1.8k citations Anantha Prasad, Louis R. Iverson et al. profile →
  4. Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships
    2015 787 citations Junshui Ma, Robert P. Sheridan et al. Journal of Chemical Information and Modeling profile →
  5. Extreme Gradient Boosting as a Method for Quantitative Structure–Activity Relationships
    2016 385 citations Robert P. Sheridan, Wei Min Wang et al. Journal of Chemical Information and Modeling profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Andy Liaw United States 18 4.3k 3.8k 3.1k 2.7k 2.5k 32 21.2k
Richard A. Olshen United States 41 3.3k 0.8× 3.9k 1.0× 2.8k 0.9× 2.5k 0.9× 12.0k 4.7× 119 43.3k
Kurt Hornik Austria 61 2.0k 0.5× 2.4k 0.7× 2.1k 0.7× 2.4k 0.9× 11.9k 4.7× 269 39.7k
Matthew C. Wiener United States 15 3.4k 0.8× 2.3k 0.6× 2.3k 0.8× 2.0k 0.7× 1.9k 0.8× 26 15.8k
Achim Zeileis Austria 56 5.6k 1.3× 2.1k 0.6× 5.0k 1.6× 1.9k 0.7× 2.7k 1.1× 224 27.8k
B. D. Ripley United Kingdom 48 8.5k 2.0× 3.9k 1.0× 6.2k 2.0× 3.3k 1.2× 5.8k 2.3× 168 50.8k
Bernard De Baets Belgium 64 1.8k 0.4× 1.3k 0.3× 1.7k 0.6× 2.1k 0.8× 3.6k 1.4× 875 19.0k
Peter J. Rousseeuw Belgium 61 1.7k 0.4× 3.9k 1.0× 2.3k 0.8× 2.4k 0.9× 11.0k 4.3× 195 52.8k
W. J. Conover United States 31 2.8k 0.7× 1.5k 0.4× 2.7k 0.9× 1.9k 0.7× 2.1k 0.8× 71 29.2k
Sanford Weisberg United States 43 4.9k 1.1× 1.6k 0.4× 3.2k 1.1× 890 0.3× 2.0k 0.8× 149 29.3k
William S. Cleveland United States 46 1.8k 0.4× 1.9k 0.5× 3.0k 1.0× 1.5k 0.6× 3.5k 1.4× 141 28.0k

Countries citing papers authored by Andy Liaw

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Andy Liaw

This figure shows the co-authorship network connecting the top 25 collaborators of Andy Liaw. A scholar is included among the top collaborators of Andy Liaw based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Andy Liaw. Andy Liaw is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ferrari, Federico, Michael O. Dillon, Andy Liaw, et al.. (2025). Bayesian hierarchical model predicts biopharmaceutical stability indicators and shelf life with application to multivalent human papillomavirus vaccine. Scientific Reports. 15(1). 17333–17333.
2.
Christensen, Melodie, Yuting Xu, Eugene E. Kwan, et al.. (2024). Dynamic sampling in autonomous process optimization. Chemical Science. 15(19). 7160–7169. 3 indexed citations
3.
Gathiaka, Symon, Sung‐Sau So, Xiaomei Chai, et al.. (2023). Discovery of non-boronic acid Arginase 1 inhibitors through virtual screening and biophysical methods. Bioorganic & Medicinal Chemistry Letters. 84. 129193–129193. 2 indexed citations
4.
Yabut, Jocelyn, et al.. (2022). Selection of an Optimal In Vitro Model to Assess P-gp Inhibition: Comparison of Vesicular and Bidirectional Transcellular Transport Inhibition Assays. Drug Metabolism and Disposition. 50(7). 909–922. 5 indexed citations
5.
Wang, Shubing, Andy Liaw, Yueming Chen, Yongchao Su, & Daniel Skomski. (2022). Convolutional Neural Networks Enable Highly Accurate and Automated Subvisible Particulate Classification of Biopharmaceuticals. Pharmaceutical Research. 40(6). 1447–1457. 10 indexed citations
6.
DiFranzo, Anthony, Robert P. Sheridan, Andy Liaw, & Matthew Tudor. (2020). Nearest Neighbor Gaussian Process for Quantitative Structure–Activity Relationships. Journal of Chemical Information and Modeling. 60(10). 4653–4663. 7 indexed citations
7.
Sheridan, Robert P., Prabha Karnachi, Matthew Tudor, et al.. (2020). Experimental Error, Kurtosis, Activity Cliffs, and Methodology: What Limits the Predictivity of Quantitative Structure–Activity Relationship Models?. Journal of Chemical Information and Modeling. 60(4). 1969–1982. 43 indexed citations
8.
Ruprecht, Benjamin, Julie Di Bernardo, Zhao Wang, et al.. (2020). A mass spectrometry-based proteome map of drug action in lung cancer cell lines. Nature Chemical Biology. 16(10). 1111–1119. 34 indexed citations
9.
Shen, Xun, Elizabeth B. Smith, Xi Ai, et al.. (2019). Live Cell Membranome cDNA Screen: A Novel Homogenous Live Cell Binding Assay to Study Membrane Protein-Ligand Interaction. SLAS DISCOVERY. 24(10). 978–986. 1 indexed citations
10.
Xu, Qiuwei, Liping Liu, Amy G. Aslamkhan, et al.. (2019). Can Galactose Be Converted to Glucose in HepG2 Cells? Improving the in Vitro Mitochondrial Toxicity Assay for the Assessment of Drug Induced Liver Injury. Chemical Research in Toxicology. 32(8). 1528–1544. 15 indexed citations
11.
Feng, Dai, Vladimir Svetnik, Andy Liaw, Matthew T. Pratola, & Robert P. Sheridan. (2019). Building Quantitative Structure–Activity Relationship Models Using Bayesian Additive Regression Trees. Journal of Chemical Information and Modeling. 59(6). 2642–2655. 9 indexed citations
12.
Murphy, Beth, Marija Tadin‐Strapps, Kristian K. Jensen, et al.. (2017). siRNA-mediated inhibition of SREBP cleavage-activating protein reduces dyslipidemia in spontaneously dysmetabolic rhesus monkeys. Metabolism. 71. 202–212. 9 indexed citations
13.
Sheridan, Robert P., Wei Min Wang, Andy Liaw, Junshui Ma, & Eric Gifford. (2016). Extreme Gradient Boosting as a Method for Quantitative Structure–Activity Relationships. Journal of Chemical Information and Modeling. 56(12). 2353–2360. 385 indexed citations breakdown →
14.
Ma, Junshui, Robert P. Sheridan, Andy Liaw, George E. Dahl, & Vladimir Svetnik. (2015). Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships. Journal of Chemical Information and Modeling. 55(2). 263–274. 787 indexed citations breakdown →
15.
Sietsema, Kathy E., Nathan A. Yates, Ronald C. Hendrickson, et al.. (2009). Potential biomarkers of muscle injury after eccentric exercise. Biomarkers. 15(3). 249–258. 15 indexed citations
16.
Zhao, Xuemei, Ekaterina G. Deyanova, Laura S. Lubbers, et al.. (2008). Differential Mass Spectrometry of Rat Plasma Reveals Proteins That Are Responsive to 17β-Estradiol and a Selective Estrogen Receptor Modulator PPT. Journal of Proteome Research. 7(10). 4373–4383. 8 indexed citations
17.
Iverson, Louis R., Anantha Prasad, & Andy Liaw. (2004). New machine learning tools for predictive vegetation mapping after climate change: Bagging and Random Forest perform better than Regression Tree Analysis.. 317–320. 21 indexed citations
18.
Brideau, Christine, Bert Gunter, Bill Pikounis, & Andy Liaw. (2003). Improved Statistical Methods for Hit Selection in High-Throughput Screening. SLAS DISCOVERY. 8(6). 634–647. 248 indexed citations
19.
Gunter, Bert, Christine Brideau, Bill Pikounis, & Andy Liaw. (2003). Statistical and Graphical Methods for Quality Control Determination of High-Throughput Screening Data. SLAS DISCOVERY. 8(6). 624–633. 50 indexed citations
20.
Burgess, Kevin, et al.. (1994). Combinatorial Technologies Involving Reiterative Division/Coupling/Recombination: Statistical Considerations. Journal of Medicinal Chemistry. 37(19). 2985–2987. 52 indexed citations

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Richard A. Olshen Breakdown of academic impact, for papers by Kurt Hornik Breakdown of academic impact, for papers by Matthew C. Wiener Breakdown of academic impact, for papers by Achim Zeileis Breakdown of academic impact, for papers by B. D. Ripley Breakdown of academic impact, for papers by Bernard De Baets Breakdown of academic impact, for papers by Peter J. Rousseeuw Breakdown of academic impact, for papers by W. J. Conover Breakdown of academic impact, for papers by Sanford Weisberg Breakdown of academic impact, for papers by William S. Cleveland
Rankless by CCL
2026