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John W. Davies
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2010 – 2019
- 2017
- [j9]William J. Godinez
, Imtiaz Hossain, Stanley E. Lazic, John W. Davies, Xian Zhang:
A multi-scale convolutional neural network for phenotyping high-content cellular images. Bioinform. 33(13): 2010-2019 (2017)
2000 – 2009
- 2009
- [j8]Andreas Bender, Jeremy L. Jenkins
How Similar Are Similarity Searching Methods? A Principal Component Analysis of Molecular Descriptor Space. J. Chem. Inf. Model. 49(1): 108-119 (2009) - [j7]Josef Scheiber
Gaining Insight into Off-Target Mediated Effects of Drug Candidates with a Comprehensive Systems Chemical Biology Analysis. J. Chem. Inf. Model. 49(2): 308-317 (2009) - [j6]Josef Scheiber
SPREAD - exploiting chemical features that cause differential activity behavior. Stat. Anal. Data Min. 2(2): 115-122 (2009) - 2007
- [j5]Thomas J. Crisman
Understanding False Positives in Reporter Gene Assays: in Silico Chemogenomics Approaches To Prioritize Cell-Based HTS Data. J. Chem. Inf. Model. 47(4): 1319-1327 (2007) - 2006
- [j4]Meir Glick, Jeremy L. Jenkins
Enrichment of High-Throughput Screening Data with Increasing Levels of Noise Using Support Vector Machines, Recursive Partitioning, and Laplacian-Modified Naive Bayesian Classifiers. J. Chem. Inf. Model. 46(1): 193-200 (2006) - [j3]Nidhi, Meir Glick, John W. Davies, Jeremy L. Jenkins
Prediction of Biological Targets for Compounds Using Multiple-Category Bayesian Models Trained on Chemogenomics Databases. J. Chem. Inf. Model. 46(3): 1124-1133 (2006) - [j2]Andreas Bender, Jeremy L. Jenkins
"Bayes Affinity Fingerprints" Improve Retrieval Rates in Virtual Screening and Define Orthogonal Bioactivity Space: When Are Multitarget Drugs a Feasible Concept? J. Chem. Inf. Model. 46(6): 2445-2456 (2006) - 2004
- [j1]Anthony E. Klon, Meir Glick, John W. Davies:
Application of Machine Learning To Improve the Results of High-Throughput Docking Against the HIV-1 Protease. J. Chem. Inf. Model. 44(6): 2216-2224 (2004)
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