J. Davies

发表

Andreas Bender, Meir Glick, Jeremy L. Jenkins, 2009, J. Chem. Inf. Model..

Which aspects of HTS are empirically correlated with downstream success?

Thomas J. Crisman, Z. Deng, A. Bender, 2008, Current opinion in drug discovery & development.

J. Jenkins, M. Glick, J. Davies, 2004, Journal of medicinal chemistry.

Chemogenomic data analysis: prediction of small-molecule targets and the advent of biological fingerprint.

P. Clemons, A. Bender, J. Jenkins, 2007, Combinatorial chemistry & high throughput screening.

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

J. Jenkins, M. Glick, J. Davies, 2006 .

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

Andreas Bender, Meir Glick, Jeremy L. Jenkins, 2006, J. Chem. Inf. Model..

Mapping adverse drug reactions in chemical space.

M. Milik, A. Bender, J. Jenkins, 2009, Journal of medicinal chemistry.

Bridging chemical and biological space: "target fishing" using 2D and 3D molecular descriptors.

Z. Deng, A. Bender, J. Jenkins, 2006, Journal of medicinal chemistry.

In silico target fishing: Predicting biological targets from chemical structure

A. Bender, J. Jenkins, J. Davies, 2006 .

Use of ligand based models for protein domains to predict novel molecular targets and applications to triage affinity chromatography data.

John A. Tallarico, A. Bender, J. Jenkins, 2009, Journal of proteome research.

Analysis of Pharmacology Data and the Prediction of Adverse Drug Reactions and Off‐Target Effects from Chemical Structure

A. Bender, J. Jenkins, J. Scheiber, 2007, ChemMedChem.

Rethinking molecular similarity: comparing compounds on the basis of biological activity.

Peter S. Kutchukian, Z. Deng, J. Jenkins, 2012, ACS chemical biology.

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

Anthony E. Klon, M. Glick, J. Davies, 2004, Journal of Chemical Information and Modeling.

Prioritization of high throughput screening data of compound mixtures using molecular similarity

M. Glick, J. Davies, P. Acklin, 2003 .

Combination of a naive Bayes classifier with consensus scoring improves enrichment of high-throughput docking results.

Anthony E. Klon, M. Glick, J. Davies, 2004, Journal of medicinal chemistry.

Finding more needles in the haystack: A simple and efficient method for improving high-throughput docking results.

Anthony E. Klon, M. Glick, J. Davies, 2004, Journal of medicinal chemistry.

SPREAD—exploiting chemical features that cause differential activity behavior

Andreas Bender, Meir Glick, Ben Cornett, 2009 .

Dark chemical matter as a promising starting point for drug lead discovery.

Anne Mai Wassermann, Eugen Lounkine, Meir Glick, 2015, Nature chemical biology.

Plate-Based Diversity Selection Based on Empirical HTS Data to Enhance the Number of Hits and Their Chemical Diversity

Andreas Bender, Meir Glick, Dmitri Mikhailov, 2009, Journal of biomolecular screening.

A lead discovery strategy driven by a comprehensive analysis of proteases in the peptide substrate space

Rajiv Chopra, Meir Glick, Florian Nigsch, 2010, Protein science : a publication of the Protein Society.

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

Andreas Bender, Meir Glick, Jeremy L. Jenkins, 2007, J. Chem. Inf. Model..

Cover Picture: Analysis of Pharmacology Data and the Prediction of Adverse Drug Reactions and Off-Target Effects from Chemical Structure (ChemMedChem 6/2007)

A. Bender, J. Jenkins, J. Scheiber, 2007 .

Targeting angiogenesis with a conjugate of HPMA copolymer and TNP-470

J. Davies, J. Folkman, G. Corfas, 2004, Nature Medicine.

Small Molecules for Chemogenomicsbased Drug Discovery

J. Jenkins, M. Glick, J. Davies, 2006 .

Design of small molecule libraries for NMR screening and other applications in drug discovery.

John Davies, Edgar Jacoby, Marcel J J Blommers, 2002, Current topics in medicinal chemistry.

The discovery of capsazepine, the first competitive antagonist of the sensory neuron excitants capsaicin and resiniferatoxin.

J. Davies, S. Bevan, J. Winter, 1994, Journal of medicinal chemistry.

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

Meir Glick, Jeremy L. Jenkins, John W. Davies, 2006, J. Chem. Inf. Model..

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

Xian Zhang, John W. Davies, Imtiaz Hossain, 2017, Bioinform..

The opportunities of mining historical and collective data in drug discovery.

Anne Mai Wassermann, Meir Glick, John W Davies, 2015, Drug discovery today.

Bridging Chemical and Biological Data: Implications for Pharmaceutical Drug Discovery

Ben Cornett, Jeremy L. Jenkins, Andreas Bender, 2011 .

PDEPT: polymer-directed enzyme prodrug therapy. 2. HPMA copolymer-beta-lactamase and HPMA copolymer-C-Dox as a model combination.

J. Davies, R. Satchi‐Fainaro, R. Duncan, 2003, Bioconjugate chemistry.

Pharmacology of capsaicin-, anandamide-, and N-arachidonoyl-dopamine-evoked cell death in a homogeneous transient receptor potential vanilloid subtype 1 receptor population.

J. Davies, A. Hainsworth, D. Lambert, 2010, British journal of anaesthesia.

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

Bin Chen, Andreas Bender, Meir Glick, 2009, J. Chem. Inf. Model..

“Plate Cherry Picking”: A Novel Semi-Sequential Screening Paradigm for Cheaper, Faster, Information-Rich Compound Selection

Andreas Bender, Meir Glick, Christian N Parker, 2007, Journal of biomolecular screening.

Flexible 3D pharmacophores as descriptors of dynamic biological space.

Andreas Bender, Meir Glick, Alex M Clark, 2007, Journal of molecular graphics & modelling.

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, John W. Davies, 2006, J. Chem. Inf. Model..

Streamlining lead discovery by aligning in silico and high-throughput screening.

Meir Glick, Jeremy L Jenkins, John W Davies, 2006, Current opinion in chemical biology.

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

Meir Glick, John W. Davies, Anthony E. Klon, 2004, J. Chem. Inf. Model..

Enrichment of Extremely Noisy High-Throughput Screening Data Using a Naïve Bayes Classifier

Meir Glick, Pierre Acklin, Anthony E. Klon, 2004, Journal of biomolecular screening.

Chemotography for multi-target SAR analysis in the context of biological pathways.

Eugen Lounkine, Meir Glick, Paula Petrone, 2012, Bioorganic & medicinal chemistry.

"Virtual fragment linking": an approach to identify potent binders from low affinity fragment hits.

Andreas Bender, Meir Glick, Mariusz Milik, 2008, Journal of medicinal chemistry.