Andy Liaw

According to our database, Andy Liaw authored at least 16 papers between 2003 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Challenges in Variable Importance Ranking Under Correlation.

Annie Liang, Thomas Jemielita, Andy Liaw, Vladimir Svetnik, Lingkang Huang, Richard Baumgartner, Jason M. Klusowski

CoRR, 2024

2023

Development and Evaluation of Conformal Prediction Methods for QSAR.

Yuting Xu, Andy Liaw, Robert P. Sheridan, Vladimir Svetnik

CoRR, 2023

2021

Light Gradient Boosting Machine as a Regression Method for Quantitative Structure-Activity Relationships.

Robert P. Sheridan, Andy Liaw, Matthew Tudor

CoRR, 2021

2020

Deep Dive into Machine Learning Models for Protein Engineering.

Yuting Xu, Deeptak Verma, Robert P. Sheridan, Andy Liaw, Junshui Ma, Nicholas M. Marshall, John McIntosh, Edward C. Sherer, Vladimir Svetnik, Jennifer M. Johnston

J. Chem. Inf. Model., 2020

Correction to Extreme Gradient Boosting as a Method for Quantitative Structure-Activity Relationships.

Robert P. Sheridan, Min Wang, Andy Liaw, Junshi Ma, Eric M. Gifford

J. Chem. Inf. Model., 2020

Experimental Error, Kurtosis, Activity Cliffs, and Methodology: What Limits the Predictivity of Quantitative Structure-Activity Relationship Models?

Robert P. Sheridan, Prabha Karnachi, Matthew Tudor, Yuting Xu, Andy Liaw, Falgun Shah, Alan C. Cheng, Elizabeth Joshi, Meir Glick, Juan Alvarez

J. Chem. Inf. Model., 2020

Nearest Neighbor Gaussian Process for Quantitative Structure-Activity Relationships.

Anthony Difranzo, Robert P. Sheridan, Andy Liaw, Matthew Tudor

J. Chem. Inf. Model., 2020

2019

Building Quantitative Structure-Activity Relationship Models Using Bayesian Additive Regression Trees.

Dai Feng, Vladimir Svetnik, Andy Liaw, Matthew T. Pratola, Robert P. Sheridan

J. Chem. Inf. Model., 2019

2018

Profiling Diverse Chemical Space to Map the Druggable Proteome.

Huijun Wang, Francisco Garcia, An Chi, Ivan Cornella Taracido, Anne Mai Wasssermann, Andy Liaw

Proceedings of the 2018 ACM International Conference on Bioinformatics, 2018

2017

Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships.

Yuting Xu, Junshui Ma, Andy Liaw, Robert P. Sheridan, Vladimir Svetnik

J. Chem. Inf. Model., October, 2017

2016

Extreme Gradient Boosting as a Method for Quantitative Structure-Activity Relationships.

Robert P. Sheridan, Wei Min Wang, Andy Liaw, Junshui Ma, Eric M. Gifford

J. Chem. Inf. Model., 2016

2015

Deep Neural Nets as a Method for Quantitative Structure-Activity Relationships.

Junshui Ma, Robert P. Sheridan, Andy Liaw, George E. Dahl, Vladimir Svetnik

J. Chem. Inf. Model., 2015

2009

Generating hypotheses about molecular structure-activity relationships (SARs) by solving an optimization problem.

Junshui Ma, Christopher Tong, Andy Liaw, Robert P. Sheridan, John Szumiloski, Vladimir Svetnik

Stat. Anal. Data Min., 2009

2005

Boosting: An Ensemble Learning Tool for Compound Classification and QSAR Modeling.

Vladimir Svetnik, Ting Wang, Christopher Tong, Andy Liaw, Robert P. Sheridan, Qinghua Song

J. Chem. Inf. Model., 2005

2004

Application of Breiman's Random Forest to Modeling Structure-Activity Relationships of Pharmaceutical Molecules.

Vladimir Svetnik, Andy Liaw, Christopher Tong, Ting Wang

Proceedings of the Multiple Classifier Systems, 5th International Workshop, 2004

2003

Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling.

Vladimir Svetnik, Andy Liaw, Christopher Tong, J. Christopher Culberson, Robert P. Sheridan, Bradley P. Feuston

J. Chem. Inf. Comput. Sci., 2003