John W. Davies

According to our database, John W. Davies authored at least 9 papers between 2004 and 2017.

Collaborative distances:

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

2017

A multi-scale convolutional neural network for phenotyping high-content cellular images.

William J. Godinez, Imtiaz Hossain, Stanley E. Lazic, John W. Davies, Xian Zhang

Bioinform., 2017

2009

SPREAD - exploiting chemical features that cause differential activity behavior.

Josef Scheiber, Jeremy L. Jenkins, Andreas Bender, Mariusz Milik, Dmitri Mikhailov, Sai Chetan K. Sukuru, Ben Cornett, Steven Whitebread, Laszlo Urban, John W. Davies, Meir Glick

Stat. Anal. Data Min., 2009

Gaining Insight into Off-Target Mediated Effects of Drug Candidates with a Comprehensive Systems Chemical Biology Analysis.

Josef Scheiber, Bin Chen, Mariusz Milik, Sai Chetan K. Sukuru, Andreas Bender, Dmitri Mikhailov, Steven Whitebread, Jacques Hamon, Kamal Azzaoui, Laszlo Urban, Meir Glick, John W. Davies, Jeremy L. Jenkins

J. Chem. Inf. Model., 2009

How Similar Are Similarity Searching Methods? A Principal Component Analysis of Molecular Descriptor Space.

Andreas Bender, Jeremy L. Jenkins, Josef Scheiber, Sai Chetan K. Sukuru, Meir Glick, John W. Davies

J. Chem. Inf. Model., 2009

2007

Understanding False Positives in Reporter Gene Assays: in Silico Chemogenomics Approaches To Prioritize Cell-Based HTS Data.

Thomas J. Crisman, Christian N. Parker, Jeremy L. Jenkins, Josef Scheiber, Mathis Thoma, Zhao Bin Kang, Richard Kim, Andreas Bender, James H. Nettles, John W. Davies, Meir Glick

J. Chem. Inf. Model., 2007

2006

Prediction of Biological Targets for Compounds Using Multiple-Category Bayesian Models Trained on Chemogenomics Databases.

Nidhi, Meir Glick, John W. Davies, Jeremy L. Jenkins

J. Chem. Inf. Model., 2006

Enrichment of High-Throughput Screening Data with Increasing Levels of Noise Using Support Vector Machines, Recursive Partitioning, and Laplacian-Modified Naive Bayesian Classifiers.

Meir Glick, Jeremy L. Jenkins, James H. Nettles, Hamilton Hitchings, John W. Davies

J. Chem. Inf. Model., 2006

"Bayes Affinity Fingerprints" Improve Retrieval Rates in Virtual Screening and Define Orthogonal Bioactivity Space: When Are Multitarget Drugs a Feasible Concept?

Andreas Bender, Jeremy L. Jenkins, Meir Glick, Zhan Deng, James H. Nettles, John W. Davies

J. Chem. Inf. Model., 2006

2004

Application of Machine Learning To Improve the Results of High-Throughput Docking Against the HIV-1 Protease.

Anthony E. Klon, Meir Glick, John W. Davies

J. Chem. Inf. Model., 2004