Meir Glick
According to our database1,
Meir Glick
authored at least 16 papers
between 1993 and 2022.
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Bibliography
2022
PepSeA: Peptide Sequence Alignment and Visualization Tools to Enable Lead Optimization.
J. Chem. Inf. Model., 2022
2020
Experimental Error, Kurtosis, Activity Cliffs, and Methodology: What Limits the Predictivity of Quantitative Structure-Activity Relationship Models?
J. Chem. Inf. Model., 2020
2016
Public Domain HTS Fingerprints: Design and Evaluation of Compound Bioactivity Profiles from PubChem's Bioassay Repository.
J. Chem. Inf. Model., 2016
2015
Experimental Design Strategy: Weak Reinforcement Leads to Increased Hit Rates and Enhanced Chemical Diversity.
J. Chem. Inf. Model., 2015
2013
Bioturbo Similarity Searching: Combining Chemical and Biological Similarity To Discover Structurally Diverse Bioactive Molecules.
J. Chem. Inf. Model., 2013
2011
Activity-Aware Clustering of High Throughput Screening Data and Elucidation of Orthogonal Structure-Activity Relationships.
J. Chem. Inf. Model., 2011
2009
Stat. Anal. Data Min., 2009
Gaining Insight into Off-Target Mediated Effects of Drug Candidates with a Comprehensive Systems Chemical Biology Analysis.
J. Chem. Inf. Model., 2009
How Similar Are Similarity Searching Methods? A Principal Component Analysis of Molecular Descriptor Space.
J. Chem. Inf. Model., 2009
2007
Understanding False Positives in Reporter Gene Assays: in Silico Chemogenomics Approaches To Prioritize Cell-Based HTS Data.
J. Chem. Inf. Model., 2007
2006
Prediction of Biological Targets for Compounds Using Multiple-Category Bayesian Models Trained on Chemogenomics Databases.
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.
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?
J. Chem. Inf. Model., 2006
2004
Application of Machine Learning To Improve the Results of High-Throughput Docking Against the HIV-1 Protease.
J. Chem. Inf. Model., 2004
2002
1993
Extending crystallographic information with semiempirical quantum mechanics and molecular mechanics: A case of aspartic proteinases.
J. Chem. Inf. Comput. Sci., 1993