A recursive-partitioning model for blood–brain barrier permeation
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Summary
A series of bagged recursive partitioning models for log(BB) is presented and low correlation coefficients for this test set are improved when compounds known to be P-gp substrates or statistical extrapolations are removed.
- Type
- article
- Published
- 2005-12-06
- Cited by
- 53
- References
- 101
- OpenAlex
- https://openalex.org/W1980435769
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:11960834
Keywords
Series (stratigraphy), Correlation, Recursive partitioning, Mathematics, Biological system
References
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Cited by
- Applied Predictive Modeling
- Tuning the predictive capacity of the PAMPA-BBB model.
- A Genetic Algorithm Based Support Vector Machine Model for Blood-Brain Barrier Penetration Prediction
- Prediction of passive blood-brain partitioning: straightforward and effective classification models based on in silico derived physicochemical descriptors
- Discovery of agonists of cannabinoid receptor 1 with restricted central nervous system penetration aimed for treatment of gastroesophageal reflux disease.
- Computer Calculation of Drug Penetration Through the Blood–Brain Barrier
- In vitro formulation optimization of intranasal galantamine leading to enhanced bioavailability and reduced emetic response in vivo.
- Transport processes in biological systems: Tumoral cells and human brain
- The use of machine learning and nonlinear statistical tools for ADME prediction
- Qualitative prediction of blood–brain barrier permeability on a large and refined dataset
- Machine-learning approaches in drug discovery: methods and applications.
- Strategies to optimize the brain availability of central nervous system drug candidates
- Development of a computational approach to predict blood-brain permeability on anti-viral Nucleoside Analogues
- Brain drug targeting: a computational approach for overcoming blood-brain barrier.
- Statistical Confidence for Variable Selection in QSAR Models via Monte Carlo Cross-Validation
- Strategies to minimize CNS toxicity: in vitro high-throughput assays and computational modeling
- Identification of Novel Functional Inhibitors of Acid Sphingomyelinase
- In SilicoPrediction of Blood–Brain Partitioning Using a Chemometric Method Called Genetic Algorithm Based Variable Selection
- On semi-supervised linear regression in covariate shift problems
- Getting the MAX out of Computational Models: The Prediction of Unbound-Brain and Unbound-Plasma Maximum Concentrations.
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