Andy Liaw - RankMe

17 papers Journal 15Unranked 2

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	A novel machine learning based framework for developing composite digital biomarkers of disease progression. Frontiers Digit. Health Song Zhai, Andy Liaw, Judong Shen, Yuting Xu, Vladimir Svetnik, James J. Fitzgerald, Chrystalina A. Antoniades, Dan Holder, Marissa F. Dockendorf, Jie Ren, Richard Baumgartner
2024	J	`jnl`	Challenges in Variable Importance Ranking Under Correlation. CoRR Annie Liang, Thomas Jemielita, Andy Liaw, Vladimir Svetnik, Lingkang Huang, Richard Baumgartner, Jason M. Klusowski
2023	J	`jnl`	Development and Evaluation of Conformal Prediction Methods for QSAR. CoRR Yuting Xu, Andy Liaw, Robert P. Sheridan, Vladimir Svetnik
2021	J	`jnl`	Light Gradient Boosting Machine as a Regression Method for Quantitative Structure-Activity Relationships. CoRR Robert P. Sheridan, Andy Liaw, Matthew Tudor
2020	J	`jnl`	Correction to Extreme Gradient Boosting as a Method for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. Robert P. Sheridan, Min Wang, Andy Liaw, Junshi Ma, Eric M. Gifford
2020	J	`jnl`	Deep Dive into Machine Learning Models for Protein Engineering. J. Chem. Inf. Model. Yuting Xu, Deeptak Verma, Robert P. Sheridan, Andy Liaw, Junshui Ma, Nicholas M. Marshall, John McIntosh, Edward C. Sherer, Vladimir Svetnik, Jennifer M. Johnston
2020	J	`jnl`	Experimental Error, Kurtosis, Activity Cliffs, and Methodology: What Limits the Predictivity of Quantitative Structure-Activity Relationship Models? J. Chem. Inf. Model. Robert P. Sheridan, Prabha Karnachi, Matthew Tudor, Yuting Xu, Andy Liaw, Falgun Shah, Alan C. Cheng, Elizabeth Joshi, Meir Glick, Juan Alvarez
2020	J	`jnl`	Nearest Neighbor Gaussian Process for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. Anthony Difranzo, Robert P. Sheridan, Andy Liaw, Matthew Tudor
2019	J	`jnl`	Building Quantitative Structure-Activity Relationship Models Using Bayesian Additive Regression Trees. J. Chem. Inf. Model. Dai Feng, Vladimir Svetnik, Andy Liaw, Matthew T. Pratola, Robert P. Sheridan
2018	—	`conf`	Profiling Diverse Chemical Space to Map the Druggable Proteome. BCB Huijun Wang, Francisco Garcia, An Chi, Ivan Cornella Taracido, Anne Mai Wasssermann, Andy Liaw
2017	J	`jnl`	Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. Yuting Xu, Junshui Ma, Andy Liaw, Robert P. Sheridan, Vladimir Svetnik
2016	J	`jnl`	Extreme Gradient Boosting as a Method for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. Robert P. Sheridan, Wei Min Wang, Andy Liaw, Junshui Ma, Eric M. Gifford
2015	J	`jnl`	Deep Neural Nets as a Method for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. Junshui Ma, Robert P. Sheridan, Andy Liaw, George E. Dahl, Vladimir Svetnik
2009	J	`jnl`	Generating hypotheses about molecular structure-activity relationships (SARs) by solving an optimization problem. Stat. Anal. Data Min. Junshui Ma, Christopher Tong, Andy Liaw, Robert P. Sheridan, John Szumiloski, Vladimir Svetnik
2005	J	`jnl`	Boosting: An Ensemble Learning Tool for Compound Classification and QSAR Modeling. J. Chem. Inf. Model. Vladimir Svetnik, Ting Wang, Christopher Tong, Andy Liaw, Robert P. Sheridan, Qinghua Song
2004	—	`conf`	Application of Breiman's Random Forest to Modeling Structure-Activity Relationships of Pharmaceutical Molecules. Multiple Classifier Systems Vladimir Svetnik, Andy Liaw, Christopher Tong, Ting Wang
2003	J	`jnl`	Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling. J. Chem. Inf. Comput. Sci. Vladimir Svetnik, Andy Liaw, Christopher Tong, J. Christopher Culberson, Robert P. Sheridan, Bradley P. Feuston