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QSAR Modeling Using Automatically Updating Correction Libraries: Application to a Human Plasma Protein Binding Model

https://doi.org/10.1021/ci700197x
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What this work says

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

inferredcites →https://doi.org/10.1002/9783906390468openalex-snapshot
Pharmacokinetic Profiling in Drug Research
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Application of ALOGPS to predict 1‐octanol/water distribution coefficients, logP, and logD, of AstraZeneca in‐house database
inferredcites →https://doi.org/10.1002/qsar.200610093openalex-snapshot
ADMET Property Prediction: The State of the Art and Current Challenges
inferredcites →https://doi.org/10.1002/qsar.200630114openalex-snapshot
Time‐Series QSAR Analysis of Human Plasma Protein Binding Data
inferredcites →https://doi.org/10.1007/s10822-005-9029-8openalex-snapshot
Automated QSPR through Competitive Workflow
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Can we estimate the accuracy of ADME–Tox predictions?
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Neighborhood Behavior: A Useful Concept for Validation of “Molecular Diversity” Descriptors
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In silico ADME/Tox: why models fail
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ADMET in silico modelling: towards prediction paradise?

What points at this work

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

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Large‐Scale Evaluation of log P Predictors: Local Corrections May Compensate Insufficient Accuracy and Need of Experimentally Testing Every Other Compound
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ChemInform Abstract: QSAR Modeling Using Automatically Updating Correction Libraries: Application to a Human Plasma Protein Binding Model.
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Forecasting CYP2D6 and CYP3A4 Risk with a Global/Local Fusion Model of CYP450 Inhibition
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Predictivity of Simulated ADME AutoQSAR Models over Time
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Automated QSAR with a Hierarchy of Global and Local Models
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AutoWeka: Toward an Automated Data Mining Software for QSAR and QSPR Studies
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Remember to Correct the Bias When Using Deep Learning for Regression!
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In Silico Prediction of Plasma and Tissue Protein Binding
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Quantitative Approaches to Structure–Activity Relationships
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In Silico Prediction of Plasma and Tissue Protein Binding
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Assessment of applicability domain for multivariate counter-propagation artificial neural network predictive models by minimum Euclidean distance space analysis: A case study
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ADME properties evaluation in drug discovery: Prediction of plasma protein binding using NSGA-II combining PLS and consensus modeling
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A chemistry wiki to facilitate and enhance compound design in drug discovery
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Recent advances in computational modelling, artificial intelligence, and in silico strategies for predicting adverse effects in skincare safety: A critical review
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The importance of the domain of applicability in QSAR modeling
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Computational Analysis of Structure–Activity Relationships
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Predicting ADME properties in drug discovery
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Bias-Correction of Regression Models: A Case Study on hERG Inhibition
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Application of In Silico, In Vitro and Preclinical Pharmacokinetic Data for the Effective and Efficient Prediction of Human Pharmacokinetics
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Prediction of Glucuronidation (UGT) clearance using alamethicin activated human liver microsomes
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Prediction of Efficacious Inhalation Lung Doses via the Use of In Silico Lung Retention Quantitative Structure-Activity Relationship Models and In Vitro Potency Screens
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Computational methods and software in computer-aided combinatorial library design
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Rapid Screening of Drug-Protein Binding Using High-Performance Affinity Chromatography with Columns Containing Immobilized Human Serum Albumin
inferred← citeshttps://doi.org/10.1517/17460441.2011.560604openalex-snapshot
The 18th European Symposium on Quantitative Structure–Activity Relationships
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Molecular Similarity and Xenobiotic Metabolism
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Two-Dimensional (2D) In Silico Models for Absorption, Distribution, Metabolism, Excretion and Toxicity (ADME/T) in Drug Discovery
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