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Learning from the Data: Mining of Large High-Throughput Screening Databases

https://doi.org/10.1021/ci060102u
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1001/jama.294.11.1399openalex-snapshot
Realizing the Promise of Genomics in Biomedical Research
inferredcites →https://doi.org/10.1002/3527603948openalex-snapshot
Chemogenomics in Drug Discovery
inferredcites →https://doi.org/10.1002/prot.20392openalex-snapshot
Linking tumor cell cytotoxicity to mechanism of drug action: An integrated analysis of gene expression, small‐molecule screening and structural databases
inferredcites →https://doi.org/10.1002/qsar.200330860openalex-snapshot
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inferredcites →https://doi.org/10.1007/bf03380186openalex-snapshot
Challenges and prospects for computational aids to molecular diversity
inferredcites →https://doi.org/10.1016/j.chembiol.2003.08.009openalex-snapshot
Biological Mechanism Profiling Using an Annotated Compound Library
inferredcites →https://doi.org/10.1016/j.mce.2003.10.008openalex-snapshot
The 45-year story of the development of an anti-aldosterone more specific than spironolactone
inferredcites →https://doi.org/10.1016/j.tibtech.2005.07.003openalex-snapshot
Response to Froloff: Probing system structure–effect relationships
inferredcites →https://doi.org/10.1016/j.tibtech.2005.07.004openalex-snapshot
Probing drug action using in vitro pharmacological profiles
inferredcites →https://doi.org/10.1016/s1093-3263(98)00008-4openalex-snapshot
Comparison of algorithms for dissimilarity-based compound selection
inferredcites →https://doi.org/10.1016/s1359-6446(05)03477-xopenalex-snapshot
Kinomics: characterizing the therapeutically validated kinase space
inferredcites →https://doi.org/10.1016/s1367-5931(98)80014-8openalex-snapshot
Discovery of protease inhibitors using targeted libraries
inferredcites →https://doi.org/10.1021/ci025569topenalex-snapshot
Similarity Metrics for Ligands Reflecting the Similarity of the Target Proteins
inferredcites →https://doi.org/10.1021/ci025586iopenalex-snapshot
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inferredcites →https://doi.org/10.1021/ci025634zopenalex-snapshot
Neighborhood Behavior of in Silico Structural Spaces with Respect to in Vitro Activity Spaces−A Novel Understanding of the Molecular Similarity Principle in the Context of Multiple Receptor Binding Profiles
inferredcites →https://doi.org/10.1021/ci025635ropenalex-snapshot
Neighborhood Behavior of in Silico Structural Spaces with Respect to In Vitro Activity Spaces−A Benchmark for Neighborhood Behavior Assessment of Different in Silico Similarity Metrics
inferredcites →https://doi.org/10.1021/ci0496954openalex-snapshot
Molecular Property eXplorer: A Novel Approach to Visualizing SAR Using Tree-Maps and Heatmaps
inferredcites →https://doi.org/10.1021/ci0502808openalex-snapshot
Novel Statistical Approach for Primary High-Throughput Screening Hit Selection
inferredcites →https://doi.org/10.1021/jm010533yopenalex-snapshot
A Common Mechanism Underlying Promiscuous Inhibitors from Virtual and High-Throughput Screening
inferredcites →https://doi.org/10.1021/jm020427bopenalex-snapshot
Kinase Inhibitors: Not Just for Kinases Anymore
inferredcites →https://doi.org/10.1021/jm030191ropenalex-snapshot
Identification and Prediction of Promiscuous Aggregating Inhibitors among Known Drugs
inferredcites →https://doi.org/10.1021/jm960290nopenalex-snapshot
Neighborhood Behavior: A Useful Concept for Validation of “Molecular Diversity” Descriptors
inferredcites →https://doi.org/10.1038/437491aopenalex-snapshot
A new grammar for drug discovery
inferredcites →https://doi.org/10.1038/nature03196openalex-snapshot
Exploring biology with small organic molecules
inferredcites →https://doi.org/10.1038/nrc1317openalex-snapshot
Microtubules as a target for anticancer drugs
inferredcites →https://doi.org/10.1038/nrg1317openalex-snapshot
Chemogenomics: an emerging strategy for rapid target and drug discovery
inferredcites →https://doi.org/10.1038/sj.tpj.6500116openalex-snapshot
Pharmacogenomic analysis: correlating molecular substructure classes with microarray gene expression data
inferredcites →https://doi.org/10.1073/pnas.0407790101openalex-snapshot
Biological spectra analysis: Linking biological activity profiles to molecular structure
inferredcites →https://doi.org/10.1093/bioinformatics/bti111openalex-snapshot
In silicogene function prediction using ontology-based pattern identification
inferredcites →https://doi.org/10.1111/j.2517-6161.1995.tb02031.xopenalex-snapshot
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
inferredcites →https://doi.org/10.1124/pr.56.2.6openalex-snapshot
Anthracyclines: Molecular Advances and Pharmacologic Developments in Antitumor Activity and Cardiotoxicity
inferredcites →https://doi.org/10.1126/science.1084564openalex-snapshot
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inferredcites →https://doi.org/10.1126/science.1084566openalex-snapshot
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inferredcites →https://doi.org/10.1126/science.275.5298.343openalex-snapshot
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inferredcites →https://doi.org/10.1385/1-59259-802-1:051openalex-snapshot
Evaluation of Molecular Similarity and Molecular Diversity Methods Using Biological Activity Data
inferredcites →https://doi.org/10.1385/1-59259-802-1:085openalex-snapshot
Application of Chemoinformatics to High-Throughput Screening
inferredcites →https://doi.org/10.1385/1-59259-802-1:317openalex-snapshot
Using Recursive Partitioning Analysis to Evaluate Compound Selection Methods
inferredcites →https://doi.org/10.2174/138620703771981214openalex-snapshot
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inferredcites →https://doi.org/10.2174/1386207043328625openalex-snapshot
The Different Strategies for Designing GPCR and Kinase Targeted Libraries
inferredcites →https://doi.org/10.2174/138620704772884832openalex-snapshot
(Research Papers) Design of a Compound Screening Collection for use in High Throughput Screening
inferredcites →https://doi.org/10.2174/1568026053828376openalex-snapshot
Key Aspects of the Novartis Compound Collection Enhancement Project for the Compilation of a Comprehensive Chemogenomics Drug Discovery Screening Collection
inferredcites →https://doi.org/10.2307/2265725openalex-snapshot
Biostatistical Analysis

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/9780470567623.ch3openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/9780470567623.ch7openalex-snapshot
Mining High‐Throughput Screening Data by Novel Knowledge‐Based Optimization Analysis
inferred← citeshttps://doi.org/10.1002/9780470571224.pse426openalex-snapshot
High‐Throughput Screening for Small‐Molecule Drug Discovery
inferred← citeshttps://doi.org/10.1002/9780470571224.pse428openalex-snapshot
Molecular Screening for Therapeutic Agents
inferred← citeshttps://doi.org/10.1002/9783527655984.ch06openalex-snapshot
The Role of Data Mining in the Identification of Bioactive Compounds via High‐Throughput Screening
inferred← citeshttps://doi.org/10.1002/btpr.2693openalex-snapshot
Identifying new clotting factor XIa inhibitors in virtual high‐throughput screens using PCA‐GA‐SVM models and signature
inferred← citeshttps://doi.org/10.1002/chin.200707209openalex-snapshot
Learning from the Data: Mining of Large High‐Throughput Screening Databases.
inferred← citeshttps://doi.org/10.1007/978-1-4939-7724-6_14openalex-snapshot
Data Mining and Computational Modeling of High-Throughput Screening Datasets
inferred← citeshttps://doi.org/10.1007/978-1-60761-839-3_17openalex-snapshot
The Interweaving of Cheminformatics and HTS
inferred← citeshttps://doi.org/10.1007/978-3-030-00545-0_9openalex-snapshot
Virtual Screening for the Discovery of Active Principles from Natural Products
inferred← citeshttps://doi.org/10.1016/b978-0-12-374194-3.00023-8openalex-snapshot
Quantitative Approaches to Structure–Activity Relationships
inferred← citeshttps://doi.org/10.1016/j.cbpa.2008.02.015openalex-snapshot
New directions in library design and analysis
inferred← citeshttps://doi.org/10.1016/j.cbpa.2008.03.015openalex-snapshot
Coverage and bias in chemical library design
inferred← citeshttps://doi.org/10.1016/j.ces.2016.02.037openalex-snapshot
Developing an in silico pipeline for faster drug candidate discovery: Virtual high throughput screening with the Signature molecular descriptor using support vector machine models
inferred← citeshttps://doi.org/10.1016/j.compbiolchem.2018.12.006openalex-snapshot
Virtual high-throughput screens identifying hPK-M2 inhibitors: Exploration of model extrapolation
inferred← citeshttps://doi.org/10.1016/j.ddtec.2006.09.012openalex-snapshot
Profiling the kinome for drug discovery
inferred← citeshttps://doi.org/10.1016/j.ejmech.2010.09.001openalex-snapshot
Computational structure–activity relationship analysis of small-molecule agonists for human formyl peptide receptors
inferred← citeshttps://doi.org/10.1016/j.ejmech.2017.08.056openalex-snapshot
Identifying novel factor XIIa inhibitors with PCA-GA-SVM developed vHTS models
inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00109openalex-snapshot
bioassayR: Cross-Target Analysis of Small Molecule Bioactivity
inferred← citeshttps://doi.org/10.1021/ci300005yopenalex-snapshot
Chemical and Biological Properties of Frequent Screening Hits
inferred← citeshttps://doi.org/10.1021/ci700059gopenalex-snapshot
Recent Advances in Chemoinformatics
inferred← citeshttps://doi.org/10.1021/jm1004495openalex-snapshot
Scaffold Explorer: An Interactive Tool for Organizing and Mining Structure−Activity Data Spanning Multiple Chemotypes
inferred← citeshttps://doi.org/10.1021/jm201328eopenalex-snapshot
Latent Hit Series Hidden in High-Throughput Screening Data
inferred← citeshttps://doi.org/10.1021/ml3003296openalex-snapshot
Metal Impurities Cause False Positives in High-Throughput Screening Campaigns
inferred← citeshttps://doi.org/10.1038/sj.bjp.0707305openalex-snapshot
In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
inferred← citeshttps://doi.org/10.1039/9781847559890-00243openalex-snapshot
Advances in Biological Screening for Lead Discovery
inferred← citeshttps://doi.org/10.1039/b703924gopenalex-snapshot
Genomics, systems biology and drug development for infectious diseases
inferred← citeshttps://doi.org/10.1039/c3cs60050eopenalex-snapshot
Chemical information matters: an e-Research perspective on information and data sharing in the chemical sciences
inferred← citeshttps://doi.org/10.1111/cbdd.13457openalex-snapshot
Identifying de‐NEDDylation inhibitors: Virtual high‐throughput screens targeting SENP8
inferred← citeshttps://doi.org/10.1126/science.1211936openalex-snapshot
Imaging of Plasmodium Liver Stages to Drive Next-Generation Antimalarial Drug Discovery
inferred← citeshttps://doi.org/10.1177/1087057116654274openalex-snapshot
An Automatic Quality Control Pipeline for High-Throughput Screening Hit Identification
inferred← citeshttps://doi.org/10.1271/kagakutoseibutsu.46.859openalex-snapshot
inferred← citeshttps://doi.org/10.1273/cbij.8.85openalex-snapshot
Application of Rough Set Theory to High Throughput Screening Data for Rational Selection of Lead Compounds
inferred← citeshttps://doi.org/10.1371/journal.pone.0171413openalex-snapshot
Large-scale bioactivity analysis of the small-molecule assayed proteome
inferred← citeshttps://doi.org/10.1517/17460440903190961openalex-snapshot
High-throughput andin silicoscreenings in drug discovery
inferred← citeshttps://doi.org/10.3390/biom8020024openalex-snapshot
Pharmaceutical Machine Learning: Virtual High-Throughput Screens Identifying Promising and Economical Small Molecule Inhibitors of Complement Factor C1s
inferred← citeshttps://doi.org/10.4155/fmc.10.246openalex-snapshot
Label-Free Screening Assays: A Strategy for Finding Better Drug Candidates
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