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Atomic Local Neighborhood Flexibility Incorporation into a Structured Similarity Measure for QSAR
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/1521-3838(200210)21:4<348::aid-qsar348>3.0.co;2-dopenalex-snapshot
From Narcosis to Hyperspace: The History of QSAR
inferredcites →https://doi.org/10.1002/9783527613106openalex-snapshot
Handbook of Molecular Descriptors
inferredcites →https://doi.org/10.1002/jcc.20681openalex-snapshot
Ultrafast shape recognition to search compound databases for similar molecular shapes
inferredcites →https://doi.org/10.1002/nav.3800020109openalex-snapshot
The Hungarian method for the assignment problem
inferredcites →https://doi.org/10.1002/qsar.200510135openalex-snapshot
Kernel Functions for Attributed Molecular Graphs – A New Similarity‐Based Approach to ADME Prediction in Classification and Regression
inferredcites →https://doi.org/10.1007/978-1-4757-2440-0openalex-snapshot
The Nature of Statistical Learning Theory
inferredcites →https://doi.org/10.1016/j.neunet.2005.07.009openalex-snapshot
Graph kernels for chemical informatics
inferredcites →https://doi.org/10.1016/s0097-8485(01)00094-8openalex-snapshot
Drug design by machine learning: support vector machines for pharmaceutical data analysis
inferredcites →https://doi.org/10.1016/s0223-5234(00)00108-2openalex-snapshot
Validation of protein-based alignment in 3D quantitative structure–activity relationships with CoMFA models
inferredcites →https://doi.org/10.1021/ci00026a007openalex-snapshot
The Extent of the Relationship between the Graph-Theoretical and the Geometrical Shape Coefficients of Chemical Compounds
inferredcites →https://doi.org/10.1021/ci049641uopenalex-snapshot
Virtual Screening of Molecular Databases Using a Support Vector Machine
inferredcites →https://doi.org/10.1021/ci0505574openalex-snapshot
Development of a Chirality-Sensitive Flexibility Descriptor for 3+3D-QSAR
inferredcites →https://doi.org/10.1021/ci060138mopenalex-snapshot
The Pharmacophore Kernel for Virtual Screening with Support Vector Machines
inferredcites →https://doi.org/10.1021/ci600205gopenalex-snapshot
Accurate Solubility Prediction with Error Bars for Electrolytes: A Machine Learning Approach
inferredcites →https://doi.org/10.1021/ci600397popenalex-snapshot
One- to Four-Dimensional Kernels for Virtual Screening and the Prediction of Physical, Chemical, and Biological Properties
inferredcites →https://doi.org/10.1021/ci700107yopenalex-snapshot
A Large Descriptor Set and a Probabilistic Kernel-Based Classifier Significantly Improve Druglikeness Classification
inferredcites →https://doi.org/10.1021/ci700274ropenalex-snapshot
Kernel Approach to Molecular Similarity Based on Iterative Graph Similarity
inferredcites →https://doi.org/10.1021/ci8001233openalex-snapshot
Efficient Calculation of Molecular Properties from Simulation Using Kernel Molecular Dynamics
inferredcites →https://doi.org/10.1021/ci9501204openalex-snapshot
A Bond Flexibility Index Derived from the Constitution of Molecules
inferredcites →https://doi.org/10.1021/cr00023a012openalex-snapshot
From atoms and bonds to three-dimensional atomic coordinates: automatic model builders
inferredcites →https://doi.org/10.1021/ja00066a004openalex-snapshot
3D-QSAR of angiotensin-converting enzyme and thermolysin inhibitors: a comparison of CoMFA models based on deduced and experimentally determined active site geometries
inferredcites →https://doi.org/10.1021/ja00226a005openalex-snapshot
Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins
inferredcites →https://doi.org/10.1021/ja00544a005openalex-snapshot
A QSAR investigation of dihydrofolate reductase inhibition by Baker triazines based upon molecular shape analysis
inferredcites →https://doi.org/10.1021/ja9718937openalex-snapshot
Construction of 3D-QSAR Models Using the 4D-QSAR Analysis Formalism
inferredcites →https://doi.org/10.1021/jm00004a017openalex-snapshot
Prediction of Receptor Properties and Binding Affinity of Ligands to Benzodiazepine/GABAA Receptors Using Artificial Neural Networks
inferredcites →https://doi.org/10.1021/jm00050a010openalex-snapshot
Molecular Similarity Indices in a Comparative Analysis (CoMSIA) of Drug Molecules to Correlate and Predict Their Biological Activity
inferredcites →https://doi.org/10.1021/jm000941mopenalex-snapshot
GRid-INdependent Descriptors (GRIND): A Novel Class of Alignment-Independent Three-Dimensional Molecular Descriptors
inferredcites →https://doi.org/10.1021/jm00145a002openalex-snapshot
A computational procedure for determining energetically favorable binding sites on biologically important macromolecules
inferredcites →https://doi.org/10.1021/jm0101343openalex-snapshot
Three-Dimensional Quantitative Structure−Activity Relationships of Cyclo-oxygenase-2 (COX-2) Inhibitors: A Comparative Molecular Field Analysis
inferredcites →https://doi.org/10.1021/jm020808popenalex-snapshot
DrugScore Meets CoMFA: Adaptation of Fields for Molecular Comparison (AFMoC) or How to Tailor Knowledge-Based Pair-Potentials to a Particular Protein
inferredcites →https://doi.org/10.1021/jm0311240openalex-snapshot
Incorporating Molecular Shape into the Alignment-free GRid-INdependent Descriptors
inferredcites →https://doi.org/10.1021/jm049113+openalex-snapshot
Anchor−GRIND: Filling the Gap between Standard 3D QSAR and the GRid-INdependent Descriptors
inferredcites →https://doi.org/10.1021/jm049157iopenalex-snapshot
Ligand-Based Prediction of Active Conformation by 3D-QSAR Flexibility Descriptors and Their Application in 3+3D-QSAR Models
inferredcites →https://doi.org/10.1021/jm0497141openalex-snapshot
A Comparison of Methods for Modeling Quantitative Structure−Activity Relationships
inferredcites →https://doi.org/10.1021/jm950589qopenalex-snapshot
Comparative Molecular Moment Analysis (CoMMA): 3D-QSAR without Molecular Superposition
inferredcites →https://doi.org/10.1021/jm970732aopenalex-snapshot
Three-Dimensional Quantitative Similarity−Activity Relationships (3D QSiAR) from SEAL Similarity Matrices
inferredcites →https://doi.org/10.1021/jm981062ropenalex-snapshot
Three-Dimensional Quantitative Structure−Activity Relationship Analyses Using Comparative Molecular Field Analysis and Comparative Molecular Similarity Indices Analysis To Elucidate Selectivity Differences of Inhibitors Binding to Trypsin, Thrombin, and Factor Xa
inferredcites →https://doi.org/10.1021/mp0700413openalex-snapshot
Machine Learning Models for Lipophilicity and Their Domain of Applicability
inferredcites →https://doi.org/10.1023/b:jcam.0000047814.85293.daopenalex-snapshot
Three-dimensional quantitative structure-activity and structure-selectivity relationships of dihydrofolate reductase inhibitors
inferredcites →https://doi.org/10.1038/194178b0openalex-snapshot
Correlation of Biological Activity of Phenoxyacetic Acids with Hammett Substituent Constants and Partition Coefficients
inferredcites →https://doi.org/10.1093/bioinformatics/bth141openalex-snapshot
Protein homology detection using string alignment kernels
inferredcites →https://doi.org/10.1093/bioinformatics/bti1055openalex-snapshot
Kernels for small molecules and the prediction of mutagenicity, toxicity and anti-cancer activity
inferredcites →https://doi.org/10.1093/bioinformatics/btm298openalex-snapshot
Classification of small molecules by two- and three-dimensional decomposition kernels
inferredcites →https://doi.org/10.1107/s0567739476001873openalex-snapshot
A solution for the best rotation to relate two sets of vectors
inferredcites →https://doi.org/10.1145/959242.959248openalex-snapshot
A survey of kernels for structured data
inferredcites →https://doi.org/10.1198/tech.2004.s743openalex-snapshot
Applied Statistics and Probability for Engineers
inferredcites →https://doi.org/10.2174/1389557013407061openalex-snapshot
Quantitative Structure-Activity Relationship (QSAR) Paradigm - Hansch Era to New Millennium
inferredcites →https://doi.org/10.48550/arxiv.0801.4061openalex-snapshot
The optimal assignment kernel is not positive definite
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/minf.200900080openalex-snapshot
Graph Kernels for Molecular Similarity
inferred← citeshttps://doi.org/10.1002/minf.201000036openalex-snapshot
Probabilistic Modeling of Conformational Space for 3D Machine Learning Approaches
inferred← citeshttps://doi.org/10.1007/978-1-4939-7899-1_6openalex-snapshot
Applicability Domain: A Step Toward Confident Predictions and Decidability for QSAR Modeling
inferred← citeshttps://doi.org/10.1007/978-3-642-20389-3_12openalex-snapshot
Approximation of Graph Kernel Similarities for Chemical Graphs by Kernel Principal Component Analysis
inferred← citeshttps://doi.org/10.1007/s10822-013-9637-7openalex-snapshot
QSAR model based on weighted MCS trees approach for the representation of molecule data sets
inferred← citeshttps://doi.org/10.1016/b978-0-12-801505-6.00007-7openalex-snapshot
Validation of QSAR Models
inferred← citeshttps://doi.org/10.1016/j.neucom.2010.03.008openalex-snapshot
Graph kernels for chemical compounds using topological and three-dimensional local atom pair environments
inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00419openalex-snapshot
xMaP—An Interpretable Alignment-Free Four-Dimensional Quantitative Structure–Activity Relationship Technique Based on Molecular Surface Properties and Conformer Ensembles
inferred← citeshttps://doi.org/10.1080/1062936x.2016.1231714openalex-snapshot
N-tuple topological/geometric cutoffs for 3D N-linear algebraic molecular codifications: variability, linear independence and QSAR analysis
inferred← citeshttps://doi.org/10.1186/1756-0381-6-7openalex-snapshot
Optimization and visualization of the edge weights in optimal assignment methods for virtual screening
inferred← citeshttps://doi.org/10.1186/1758-2946-1-14openalex-snapshot
Optimal assignment methods for ligand-based virtual screening
inferred← citeshttps://doi.org/10.1186/1758-2946-2-2openalex-snapshot
Estimation of the applicability domain of kernel-based machine learning models for virtual screening
inferred← citeshttps://doi.org/10.1186/1758-2946-2-s1-p38openalex-snapshot
Kernel-based estimation of the applicability domain of QSAR models
inferred← citeshttps://doi.org/10.1186/1758-2946-3-23openalex-snapshot
4D Flexible Atom-Pairs: An efficient probabilistic conformational space comparison for ligand-based virtual screening
inferred← citeshttps://doi.org/10.1186/1758-2946-3-3openalex-snapshot
jCompoundMapper: An open source Java library and command-line tool for chemical fingerprints
inferred← citeshttps://doi.org/10.26434/chemrxiv-2024-dkvf8openalex-snapshot
3D-Pharma, A Ligand-based Virtual Screening toolusing 3D Pharmacophore Fingerprints
inferred← citeshttps://doi.org/10.4018/978-1-4666-8136-1.ch005openalex-snapshot
Importance of Applicability Domain of QSAR Models
inferred← citeshttps://doi.org/10.4018/978-1-5225-1762-7.ch039openalex-snapshot
Importance of Applicability Domain of QSAR Models
inferred← citeshttps://doi.org/10.4018/978-1-61520-911-8.ch002openalex-snapshot
Optimal Assignment Kernels for ADME in Silico Prediction
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