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Quantitative Structure−Activity Relationship Studies Using Gaussian Processes

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

inferredcites →https://doi.org/10.1002/9780470125830openalex-snapshot
Reviews in Computational Chemistry
inferredcites →https://doi.org/10.1002/qsar.19950140503openalex-snapshot
QSAR Study of the Toxicity of Nitrobenzenes to Tetrahymena pyriformis
inferredcites →https://doi.org/10.1002/qsar.19960150103openalex-snapshot
Using Artificial Neural Networks to Predict Biological Activity from Simple Molecular Structural Considerations
inferredcites →https://doi.org/10.1016/0006-2952(92)90472-uopenalex-snapshot
Substituted imidazo[1,2-b]pyridazines
inferredcites →https://doi.org/10.1016/0223-5234(96)85873-9openalex-snapshot
Syntheses, pharmacological evaluation and molecular modelling of substituted 6-alkoxyimidazo[1,2-b]pyridazines as new ligands for the benzodiazepine receptor
inferredcites →https://doi.org/10.1016/s0925-2312(97)90018-7openalex-snapshot
Advances in neural information processing systems 7
inferredcites →https://doi.org/10.1021/ci000450aopenalex-snapshot
Use of Automatic Relevance Determination in QSAR Studies Using Bayesian Neural Networks
inferredcites →https://doi.org/10.1021/ci950204copenalex-snapshot
Neural Network Studies. 2. Variable Selection
inferredcites →https://doi.org/10.1021/ci980325nopenalex-snapshot
Neural Network Studies. 3. Variable Selection in the Cascade-Correlation Learning Architecture
inferredcites →https://doi.org/10.1021/ci990061kopenalex-snapshot
Nonlinear Multivariate Regression Outperforms Several Concisely Designed Neural Networks on Three QSPR Data Sets
inferredcites →https://doi.org/10.1021/ja00856a001openalex-snapshot
Characterization of molecular branching
inferredcites →https://doi.org/10.1021/ja00856a002openalex-snapshot
Importance of nonbonded attraction in the stereochemistry of the SN2' reaction
inferredcites →https://doi.org/10.1021/ja01062a035openalex-snapshot
p-σ-π Analysis. A Method for the Correlation of Biological Activity and Chemical Structure
inferredcites →https://doi.org/10.1021/jm00063a017openalex-snapshot
Structure-activity relationship studies at benzodiazepine receptor (BZR): a comparison of the substituent effects of pyrazoloquinolinone analogs
inferredcites →https://doi.org/10.1021/jm00085a016openalex-snapshot
Synthesis and muscarinic activities of quinuclidin-3-yltriazole and -tetrazole derivatives
inferredcites →https://doi.org/10.1021/jm00085a017openalex-snapshot
Muscarinic receptor subtype specificity of (N,N-dialkylamino)alkyl 2-cyclohexyl-2-phenylpropionates: cylexphenes (cyclohexyl-substituted aprophen analogs)
inferredcites →https://doi.org/10.1021/jm00090a019openalex-snapshot
Novel functional M1 selective muscarinic agonists. Synthesis and structure-activity relationships of 3-(1,2,5-thiadiazolyl)-1,2,5,6-tetrahydro-1-methylpyridines
inferredcites →https://doi.org/10.1021/jm00090a020openalex-snapshot
Nucleic acid related compounds. 74. Synthesis and biological activity of 2'(and 3')-deoxy-2'(and 3')-methylenenucleoside analogs that function as mechanism-based inhibitors of S-adenosyl-L-homocysteine hydrolase and/or ribonucleotide reductase
inferredcites →https://doi.org/10.1021/jm00106a033openalex-snapshot
Muscarinic cholinergic agonists and antagonists of the 3-(3-alkyl-1,2,4-oxadiazol-5-yl)-1,2,5,6-tetrahydropyridine type. Synthesis and structure-activity relationships
inferredcites →https://doi.org/10.1021/jm00113a009openalex-snapshot
Comparison of azabicyclic esters and oxadiazoles as ligands for the muscarinic receptor
inferredcites →https://doi.org/10.1021/jm00117a029openalex-snapshot
Synthesis of novel 3-substituted .beta.-carbolines as benzodiazepine receptor ligands: probing the benzodiazepine receptor pharmacophore
inferredcites →https://doi.org/10.1021/jm00117a030openalex-snapshot
Structure-activity relationships among benextramine-related tetraamine disulfides. Chain length effect on .alpha.-adrenoreceptor blocking activity
inferredcites →https://doi.org/10.1021/jm00165a028openalex-snapshot
Structural requirements for agonist actions at the benzodiazepine receptor: studies with analogs of 6-(benzyloxy)-4-(methoxymethyl)-.beta.-carboline-3-carboxylic acid ethyl ester
inferredcites →https://doi.org/10.1021/jm00165a029openalex-snapshot
Synthesis and structure-activity relationship of C5-substituted analogs of (.+-.)-10,11-dihydro-5H-dibenzo[a,d]cyclohepten-5, 10-imine [(.+-.)-desmethyl-MK801]: ligands for the NMDA receptor-coupled phencyclidine binding site
inferredcites →https://doi.org/10.1021/jm00346a002openalex-snapshot
2-Arylpyrazolo[4,3-c]quinolin-3-ones: a novel agonist, a partial agonist and an antagonist of benzodiazepines
inferredcites →https://doi.org/10.1021/jm980697nopenalex-snapshot
Robust QSAR Models Using Bayesian Regularized Neural Networks
inferredcites →https://doi.org/10.1021/tx9900627openalex-snapshot
A Quantitative Structure−Activity Relationships Model for the Acute Toxicity of Substituted Benzenes to Tetrahymena pyriformis Using Bayesian-Regularized Neural Networks

What points at this work

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

inferred← citeshttps://doi.org/10.1002/0470845015.cu0052openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/9783527628766.biblioopenalex-snapshot
Bibliography
inferred← citeshttps://doi.org/10.1002/bip.21091openalex-snapshot
Modeling and prediction of binding affinities between the human amphiphysin SH3 domain and its peptide ligands using genetic algorithm‐Gaussian processes
inferred← citeshttps://doi.org/10.1002/cmdc.200700041openalex-snapshot
Predicting Lipophilicity of Drug‐Discovery Molecules using Gaussian Process Models
inferred← citeshttps://doi.org/10.1002/jssc.200800739openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/minf.201700078openalex-snapshot
Development of Predictive QSAR Models of 4‐Thiazolidinones Antitrypanosomal Activity Using Modern Machine Learning Algorithms
inferred← citeshttps://doi.org/10.1002/qsar.200610093openalex-snapshot
ADMET Property Prediction: The State of the Art and Current Challenges
inferred← citeshttps://doi.org/10.1002/qua.26097openalex-snapshot
Quantitative structure‐toxicity relationship: An “in silico study” using electrophilicity and hydrophobicity as descriptors
inferred← citeshttps://doi.org/10.1002/wcms.1187openalex-snapshot
Modern 2D QSAR for drug discovery
inferred← citeshttps://doi.org/10.1007/978-1-0716-1787-8_10openalex-snapshot
Deep Neural Networks for QSAR
inferred← citeshttps://doi.org/10.1007/s00726-008-0228-1openalex-snapshot
Gaussian process: an alternative approach for QSAM modeling of peptides
inferred← citeshttps://doi.org/10.1007/s00894-019-4120-6openalex-snapshot
Investigation of 3D pharmacophore of N-benzyl benzamide molecules of melanogenesis inhibitors using a new descriptor Klopman index: uncertainties in model
inferred← citeshttps://doi.org/10.1007/s10822-008-9193-8openalex-snapshot
Automatic QSAR modeling of ADME properties: blood–brain barrier penetration and aqueous solubility
inferred← citeshttps://doi.org/10.1007/s10822-013-9639-5openalex-snapshot
QSAR with experimental and predictive distributions: an information theoretic approach for assessing model quality
inferred← citeshttps://doi.org/10.1007/s10822-026-00869-4openalex-snapshot
Quantitative structure–activity relationship characterization and modeling of length-varying bioactive peptides
inferred← citeshttps://doi.org/10.1007/s11356-014-3182-3openalex-snapshot
Comparative performance of descriptors in a multiple linear and Kriging models: a case study on the acute toxicity of organic chemicals to algae
inferred← citeshttps://doi.org/10.1007/s12257-020-0049-yopenalex-snapshot
Artificial Intelligence in Drug Discovery: A Comprehensive Review of Data-driven and Machine Learning Approaches
inferred← citeshttps://doi.org/10.1016/bs.mie.2018.09.023openalex-snapshot
Knowledge-Based Approaches to Off-Target Screening
inferred← citeshttps://doi.org/10.1016/j.aca.2011.02.004openalex-snapshot
Prediction of P2Y12 antagonists using a novel genetic algorithm-support vector machine coupled approach
inferred← citeshttps://doi.org/10.1016/j.addr.2006.08.002openalex-snapshot
Quantitative structure–pharmacokinetic/pharmacodynamic relationships
inferred← citeshttps://doi.org/10.1016/j.asoc.2017.09.040openalex-snapshot
Deep neural network in QSAR studies using deep belief network
inferred← citeshttps://doi.org/10.1016/j.bmc.2024.117834openalex-snapshot
Discovery and evaluation of novel spiroheterocyclic protective agents via a SIRT1 upregulation mechanism in cisplatin-induced premature ovarian failure
inferred← citeshttps://doi.org/10.1016/j.chemolab.2008.02.007openalex-snapshot
Pseudo receptor probes: A novel pseudo receptor-based QSAR method and application into studies on a new kind of selective vascular endothelial growth factor-2 receptor inhibitors
inferred← citeshttps://doi.org/10.1016/j.chemolab.2024.105191openalex-snapshot
Comprehensive evaluation and systematic comparison of Gaussian process (GP) modelling applications in peptide quantitative structure-activity relationship
inferred← citeshttps://doi.org/10.1016/j.infrared.2021.103987openalex-snapshot
Optimization and comparison of models for core temperature prediction of mother rabbits using infrared thermography
inferred← citeshttps://doi.org/10.1016/j.saa.2019.03.110openalex-snapshot
Rapid analysis of the Tanreqing injection by near-infrared spectroscopy combined with least squares support vector machine and Gaussian process modeling techniques
inferred← citeshttps://doi.org/10.1016/j.sbi.2018.01.006openalex-snapshot
Statistical and machine learning approaches to predicting protein–ligand interactions
inferred← citeshttps://doi.org/10.1016/s1872-2067(18)63144-4openalex-snapshot
Advancements in biocatalysis: From computational to metabolic engineering
inferred← citeshttps://doi.org/10.1021/acs.jcim.0c00443openalex-snapshot
Practical Applications of Deep Learning To Impute Heterogeneous Drug Discovery Data
inferred← citeshttps://doi.org/10.1021/acs.jcim.0c00678openalex-snapshot
Nearest Neighbor Gaussian Process for Quantitative Structure–Activity Relationships
inferred← citeshttps://doi.org/10.1021/acs.jcim.1c00458openalex-snapshot
Toward Guided Mutagenesis: Gaussian Process Regression Predicts MHC Class II Antigen Mutant Binding
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00110openalex-snapshot
The Relative Importance of Domain Applicability Metrics for Estimating Prediction Errors in QSAR Varies with Training Set Diversity
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00229openalex-snapshot
Understanding the Roles of the “Two QSARs”
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00261openalex-snapshot
Relevance Vector Machines: Sparse Classification Methods for QSAR
inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00542openalex-snapshot
Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Prediction Errors for Deep Neural Networks
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00094openalex-snapshot
Building Quantitative Structure–Activity Relationship Models Using Bayesian Additive Regression Trees
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00297openalex-snapshot
Reliable Prediction Errors for Deep Neural Networks Using Test-Time Dropout
inferred← citeshttps://doi.org/10.1021/acs.molpharmaceut.2c00027openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci034108kopenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci200409xopenalex-snapshot
Machine Learning Methods for Property Prediction in Chemoinformatics:Quo Vadis?
inferred← citeshttps://doi.org/10.1021/ci500747nopenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci600205gopenalex-snapshot
Accurate Solubility Prediction with Error Bars for Electrolytes: A Machine Learning Approach
inferred← citeshttps://doi.org/10.1021/ci7000633openalex-snapshot
Gaussian Processes: A Method for Automatic QSAR Modeling of ADME Properties
inferred← citeshttps://doi.org/10.1021/ci800290hopenalex-snapshot
Toward Novel Universal Descriptors: Charge Fingerprints
inferred← citeshttps://doi.org/10.1021/ci900396kopenalex-snapshot
Prediction of the Basicities of Pyridines in the Gas Phase and in Aqueous Solution
inferred← citeshttps://doi.org/10.1021/ci900406xopenalex-snapshot
Gaussian Processes for Classification: QSAR Modeling of ADMET and Target Activity
inferred← citeshttps://doi.org/10.1021/mp0700413openalex-snapshot
Machine Learning Models for Lipophilicity and Their Domain of Applicability
inferred← citeshttps://doi.org/10.1039/c1ee02056kopenalex-snapshot
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inferred← citeshttps://doi.org/10.1039/c3cp53204fopenalex-snapshot
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inferred← citeshttps://doi.org/10.1039/c5mh00282fopenalex-snapshot
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inferred← citeshttps://doi.org/10.1039/c5ra10729fopenalex-snapshot
Multivariate statistical analysis methods in QSAR
inferred← citeshttps://doi.org/10.1063/1.4974344openalex-snapshot
Data-driven sensitivity inference for Thomson scattering electron density measurement systems
inferred← citeshttps://doi.org/10.1080/00268976.2024.2331620openalex-snapshot
Applications of conceptual density functional theory in reference to quantitative structure–activity / property relationship
inferred← citeshttps://doi.org/10.1080/14756366.2024.2314233openalex-snapshot
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inferred← citeshttps://doi.org/10.1111/biom.12942openalex-snapshot
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inferred← citeshttps://doi.org/10.1111/cbdd.13428openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3534966openalex-snapshot
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inferred← citeshttps://doi.org/10.1186/1758-2946-6-35openalex-snapshot
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inferred← citeshttps://doi.org/10.1186/s13321-021-00571-7openalex-snapshot
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inferred← citeshttps://doi.org/10.1517/17425250902753261openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/ijms12021259openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/ph15111383openalex-snapshot
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inferred← citeshttps://doi.org/10.35940/ijitee.i1096.0789s19openalex-snapshot
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inferred← citeshttps://doi.org/10.70675/00fff70azab21z46edz8364z60031c95c00fopenalex-snapshot
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