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Optimization of Molecular Representativeness

https://doi.org/10.1021/ci400715n
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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/minf.201000061openalex-snapshot
Best Practices for QSAR Model Development, Validation, and Exploitation
inferredcites →https://doi.org/10.1007/978-1-4757-2440-0openalex-snapshot
The Nature of Statistical Learning Theory
inferredcites →https://doi.org/10.1007/bf00116251openalex-snapshot
Induction of Decision Trees
inferredcites →https://doi.org/10.1007/bf01718702openalex-snapshot
Optimization and visualization of molecular diversity of combinatorial libraries
inferredcites →https://doi.org/10.1007/s11095-008-9609-0openalex-snapshot
QSAR Modeling of the Blood–Brain Barrier Permeability for Diverse Organic Compounds
inferredcites →https://doi.org/10.1016/j.bmc.2006.03.012openalex-snapshot
Correlation of blood–brain penetration using structural descriptors
inferredcites →https://doi.org/10.1016/j.ddtec.2013.02.001openalex-snapshot
Multi-objective optimization methods in drug design
inferredcites →https://doi.org/10.1016/s0223-5234(01)01269-7openalex-snapshot
Correlation and prediction of a large blood–brain distribution data set—an LFER study
inferredcites →https://doi.org/10.1016/s1093-3263(00)00071-1openalex-snapshot
Novel algorithms for the optimization of molecular diversity of combinatorial libraries
inferredcites →https://doi.org/10.1016/s1093-3263(01)00150-4openalex-snapshot
Designing focused libraries using MoSELECT
inferredcites →https://doi.org/10.1021/ci010375jopenalex-snapshot
Combinatorial Library Design Using a Multiobjective Genetic Algorithm
inferredcites →https://doi.org/10.1021/ci025662hopenalex-snapshot
OptDesign: Extending Optimizable k-Dissimilarity Selection to Combinatorial Library Design
inferredcites →https://doi.org/10.1021/ci200186mopenalex-snapshot
A Binary Ant Colony Optimization Classifier for Molecular Activities
inferredcites →https://doi.org/10.1021/ci300338wopenalex-snapshot
Does Rational Selection of Training and Test Sets Improve the Outcome of QSAR Modeling?
inferredcites →https://doi.org/10.1021/ci960471yopenalex-snapshot
Similarity Measures for Rational Set Selection and Analysis of Combinatorial Libraries: The Diverse Property-Derived (DPD) Approach
inferredcites →https://doi.org/10.1021/ci9700337openalex-snapshot
Stochastic Algorithms for Maximizing Molecular Diversity
inferredcites →https://doi.org/10.1021/ci970282vopenalex-snapshot
OptiSim: An Extended Dissimilarity Selection Method for Finding Diverse Representative Subsets
inferredcites →https://doi.org/10.1021/ci980107uopenalex-snapshot
Balancing Representativeness Against Diversity using Optimizable K-Dissimilarity and Hierarchical Clustering
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot
Random Forests
inferredcites →https://doi.org/10.1023/a:1020837112154openalex-snapshot
Multiobjective optimization of combinatorial libraries
inferredcites →https://doi.org/10.1023/a:1020869118689openalex-snapshot
Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection
inferredcites →https://doi.org/10.1023/a:1027232610247openalex-snapshot
Novel software tools for chemical diversity
inferredcites →https://doi.org/10.1080/01621459.1963.10500845openalex-snapshot
Hierarchical Grouping to Optimize an Objective Function
inferredcites →https://doi.org/10.1111/j.2042-7158.2011.01424.xopenalex-snapshot
Size estimation of chemical space: how big is it?
inferredcites →https://doi.org/10.1126/science.220.4598.671openalex-snapshot
Optimization by Simulated Annealing
inferredcites →https://doi.org/10.1145/1656274.1656278openalex-snapshot
The WEKA data mining software
inferredcites →https://doi.org/10.1289/ehp.5758openalex-snapshot
Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs.
inferredcites →https://doi.org/10.5281/zenodo.2555798openalex-snapshot
Molecular Optimization Using Computational Multi-Objective Methods

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

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Virtual Libraries for Docking Methods: Guidelines for the Selection and the Preparation
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A comprehensive review of chemoinformatics: From molecular representation to data-driven design
inferred← citeshttps://doi.org/10.1021/acs.jcim.3c01826openalex-snapshot
Compound Classification and Consideration of Correlation with Chemical Descriptors from Articles on Antioxidant Capacity Using Natural Language Processing
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00515openalex-snapshot
A Multi-Objective Genetic Algorithm for Outlier Removal
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Drowning in diversity? A systematic way of clustering and selecting a representative set of new psychoactive substances
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Big data and artificial intelligence (AI) methodologies for computer-aided drug design (CADD)
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A reliable computational workflow for the selection of optimal screening libraries
inferred← citeshttps://doi.org/10.1186/s13321-016-0119-5openalex-snapshot
11th German Conference on Chemoinformatics (GCC 2015)
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RANdom SAmple Consensus (RANSAC) algorithm for material-informatics: application to photovoltaic solar cells
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The Efficiency of Machine Learning Algorithms in the Prediction of Drug Reactions in Clinical Settings
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Data Mining and Machine Learning Models for Predicting Drug Likeness and Their Disease or Organ Category
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