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Application of Random Forest Approach to QSAR Prediction of Aquatic Toxicity
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Recent Advances in QSAR Studies
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Structure-toxicity relationships of nitroaromatic compounds
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The effect of nitroaromatics’ composition on their toxicity in vivo: Novel, efficient non-additive 1D QSAR analysis
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Atom pairs as molecular features in structure-activity studies: definition and applications
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Random Forest Prediction of Mutagenicity from Empirical Physicochemical Descriptors
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Random Forest Models To Predict Aqueous Solubility
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Quantitative Structure−Activity Relationship Studies of [(Biphenyloxy)propyl]isoxazole Derivatives. Inhibitors of Human Rhinovirus 2 Replication
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Quantitative Structure-Activity Relationships Based on Functional and Structural Characteristics of Organic Compounds
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QSPR-based prediction of adsorption of halogenated aromatics on yellow-brown soil
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Short‐term oral toxicity of a 2,4,6‐trinltrotoluene and hexahydro‐1,3,5‐trinitro‐1,3,5‐triazine mixture in mice, rats, and dogs
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Identification of individual structural fragments of N,N′-(bis-5-nitropyrimidyl)dispirotripiperazine derivatives for cytotoxicity and antiherpetic activity allows the prediction of new highly active compounds
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Toxicity of N-substituted aromatics to acetoclastic methanogenic activity in granular sludge
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QSAR Applicability Domain Estimation by Projection of the Training Set in Descriptor Space: A Review
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Chemical Toxicity on HeLa Cells
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Pharmacophore Discovery - Lessons Learned
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Learning of Molecular Graphs in Toxicity Prediction
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BFGTP: A BERT-Guided Two-Stage Molecular Representation Learning Framework for Toxicity Prediction
inferred← citeshttps://doi.org/10.1111/cbdd.13600openalex-snapshot
Prediction of hERG K+ channel blockage using deep neural networks
inferred← citeshttps://doi.org/10.1111/cbdd.13690openalex-snapshot
The efficiency of ligand–receptor interaction information alone as new descriptors in QSAR modeling via random forest artificial neural network
inferred← citeshttps://doi.org/10.1134/s1070428014030026openalex-snapshot
QSPR Modeling of critical parameters of organic compounds belonging to different classes in terms of the simplex representation of molecular structure
inferred← citeshttps://doi.org/10.1142/s2737416524500273openalex-snapshot
Random Forests Regression and Rescoring Strategy for Identifying Inhibitors of Ubiquitin Specific Protease-7
inferred← citeshttps://doi.org/10.1186/s13321-018-0304-9openalex-snapshot
Evaluating parameters for ligand-based modeling with random forest on sparse data sets
inferred← citeshttps://doi.org/10.1186/s13321-019-0364-5openalex-snapshot
KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images
inferred← citeshttps://doi.org/10.1186/s13321-019-0383-2openalex-snapshot
SAR and QSAR modeling of a large collection of LD50 rat acute oral toxicity data
inferred← citeshttps://doi.org/10.1186/s13321-020-00468-xopenalex-snapshot
Structure–activity relationship-based chemical classification of highly imbalanced Tox21 datasets
inferred← citeshttps://doi.org/10.1186/s13321-020-0417-9openalex-snapshot
Comparison and improvement of the predictability and interpretability with ensemble learning models in QSPR applications
inferred← citeshttps://doi.org/10.1214/14-aoas778openalex-snapshot
Ensembling classification models based on phalanxes of variables with applications in drug discovery
inferred← citeshttps://doi.org/10.1248/cpb.c22-00376openalex-snapshot
Prediction of Anti-proliferation Effect of [1,2,3]Triazolo[4,5-d]pyrimidine Derivatives by Random Forest and Mix-Kernel Function SVM with PSO
inferred← citeshttps://doi.org/10.1371/journal.pcbi.1006851openalex-snapshot
Assessment of the cardiovascular adverse effects of drug-drug interactions through a combined analysis of spontaneous reports and predicted drug-target interactions
inferred← citeshttps://doi.org/10.1371/journal.pcbi.1014515openalex-snapshot
Dynamics-enhanced molecular property prediction guided by deep learning
inferred← citeshttps://doi.org/10.1371/journal.pone.0282924openalex-snapshot
Guidance for good practice in the application of machine learning in development of toxicological quantitative structure-activity relationships (QSARs)
inferred← citeshttps://doi.org/10.1504/ijdmb.2013.056082openalex-snapshot
Computational prediction of toxicity
inferred← citeshttps://doi.org/10.1517/17460441.2015.1083006openalex-snapshot
Quantitative structure–activity relationship: promising advances in drug discovery platforms
inferred← citeshttps://doi.org/10.15407/dopovidi2014.09.103openalex-snapshot
Комплексний пiдхiд до дизайну антагонiстiв тромбоксановых А2 рецепторiв
inferred← citeshttps://doi.org/10.17615/w4vm-f755openalex-snapshot
The QSARome of the receptorome: Quantitative structure-activity relationship modeling of multiple ligand sets acting at multiple receptors
inferred← citeshttps://doi.org/10.17863/cam.43757openalex-snapshot
KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images
inferred← citeshttps://doi.org/10.18524/2304-0947.2016.1(57).67514openalex-snapshot
QSAR ANALYSIS OF THE ECDYSTEROIDS’ AFFINITY BASED ON 2.5D-SIMPLEX REPRESENTATION OF THE MOLECULAR STRUCTURE
inferred← citeshttps://doi.org/10.18524/2304-0947.2022.3(83).268607openalex-snapshot
2D QSAR ANALYSIS OF BLOOD-BRAIN BARRIER PERMEABILITY FOR ORGANIC COMPOUNDS
inferred← citeshttps://doi.org/10.19080/ijesnr.2021.27.556224openalex-snapshot
Machine Learning Approach to Identify the Relationship Between Heavy Metals and Soil Parameters in Salt Marshes
inferred← citeshttps://doi.org/10.19261/cjm.2013.08(1).12openalex-snapshot
Nonexperimental Screening of the Water Solubility, Lipophilicity, Bioavailability, Mutagenicity and Toxicity of Various Pesticides with QSAR Models Aid
inferred← citeshttps://doi.org/10.20944/preprints202310.1855.v1openalex-snapshot
Leveraging Machine Learning for a Comprehensive Assessment of PFAS Nephrotoxicity
inferred← citeshttps://doi.org/10.21203/rs.3.rs-1480061/v1openalex-snapshot
A novel hybrid machine learning model for flood hazard zoning assessments
inferred← citeshttps://doi.org/10.2166/ws.2026.112openalex-snapshot
Approximation of trapping efficiency of silt ejector using machine learning-based approaches
inferred← citeshttps://doi.org/10.2174/1568026614666140929120749openalex-snapshot
Virtual Screening Strategies in Medicinal Chemistry: The State of the Art and Current Challenges
inferred← citeshttps://doi.org/10.2298/jsc200509036sopenalex-snapshot
Quantitative structure-activity relationship modelling of influenza M2 ion channels inhibitors
inferred← citeshttps://doi.org/10.25046/aj090306openalex-snapshot
Leveraging Machine Learning for a Comprehensive Assessment of PFAS Nephrotoxicity
inferred← citeshttps://doi.org/10.26434/chemrxiv-2024-zr2vropenalex-snapshot
Molecular Fingerprints Optimization for Enhanced Predictive Modeling
inferred← citeshttps://doi.org/10.26438/ijsrcse/v6i2.4150openalex-snapshot
Ensemble based J48 and random forest based C6H6 air pollution detection
inferred← citeshttps://doi.org/10.3389/fenvs.2015.00080openalex-snapshot
DeepTox: Toxicity Prediction using Deep Learning
inferred← citeshttps://doi.org/10.3390/ijms11093413openalex-snapshot
Prediction of PKCθ Inhibitory Activity Using the Random Forest Algorithm
inferred← citeshttps://doi.org/10.3390/ijms12021259openalex-snapshot
A Classification Study of Respiratory Syncytial Virus (RSV) Inhibitors by Variable Selection with Random Forest
inferred← citeshttps://doi.org/10.3390/ijms12053018openalex-snapshot
Investigations on Inhibitors of Hedgehog Signal Pathway: A Quantitative Structure-Activity Relationship Study
inferred← citeshttps://doi.org/10.3390/ijms19082358openalex-snapshot
Machine Learning Based Toxicity Prediction: From Chemical Structural Description to Transcriptome Analysis
inferred← citeshttps://doi.org/10.3390/ijms23063053openalex-snapshot
Prediction of the Neurotoxic Potential of Chemicals Based on Modelling of Molecular Initiating Events Upstream of the Adverse Outcome Pathways of (Developmental) Neurotoxicity
inferred← citeshttps://doi.org/10.3390/molecules24183383openalex-snapshot
Toxicity Prediction Method Based on Multi-Channel Convolutional Neural Network
inferred← citeshttps://doi.org/10.3390/molecules28031342openalex-snapshot
Molecular Toxicity Virtual Screening Applying a Quantized Computational SNN-Based Framework
inferred← citeshttps://doi.org/10.3390/molecules31071144openalex-snapshot
A Multitask Active Learning Framework with Probabilistic Modeling for Multi-Species Acute Toxicity Prediction
inferred← citeshttps://doi.org/10.4018/978-1-5225-0549-5.ch003openalex-snapshot
The History and Development of Quantitative Structure-Activity Relationships (QSARs)
inferred← citeshttps://doi.org/10.4018/ijqspr.2016010101openalex-snapshot
The History and Development of Quantitative Structure-Activity Relationships (QSARs)
inferred← citeshttps://doi.org/10.4018/ijqspr.2019100104openalex-snapshot
Development of Predictive Linear and Non-linear QSTR Models for Aliivibrio Fischeri Toxicity of Deep Eutectic Solvents
inferred← citeshttps://doi.org/10.4018/ijqspr.2020010101openalex-snapshot
QSPR Models for Predicting of the Melting Points and Refractive Indices for Inorganic Substances
inferred← citeshttps://doi.org/10.4155/fmc.10.194openalex-snapshot
Per Aspera Ad Astra : Application of Simplex Qsar Approach in Antiviral Research
inferred← citeshttps://doi.org/10.4155/fmc.10.278openalex-snapshot
Qsar Analysis of [(Biphenyloxy)Propyl]Isoxazoles: Agents Against Coxsackievirus B3
inferred← citeshttps://doi.org/10.48550/arxiv.2009.12199openalex-snapshot
Explaining Chemical Toxicity using Missing Features
inferred← citeshttps://doi.org/10.5688/ajpe81346openalex-snapshot
Computer-Assisted Decision Support for Student Admissions Based on Their Predicted Academic Performance
inferred← citeshttps://doi.org/10.5772/62483openalex-snapshot
Optimization Algorithms for Chemoinformatics and Material-informatics
inferred← citeshttps://doi.org/10.5772/intechopen.75602openalex-snapshot
Application of AI in Modeling of Real System in Chemistry
inferred← citeshttps://doi.org/10.6084/m9.figshare.12050823openalex-snapshot
Additional file 1 of Comparison and improvement of the predictability and interpretability with ensemble learning models in QSPR applications
inferred← citeshttps://doi.org/10.6084/m9.figshare.13151976openalex-snapshot
Additional file 1 of Structure–activity relationship-based chemical classification of highly imbalanced Tox21 datasets
inferred← citeshttps://doi.org/10.70675/282f63d1z9a3ez448dza5d3zc92891727d05openalex-snapshot
Estimation de l'écotoxicité de substances chimiques par des méthodes à noyaux
inferred← citeshttps://doi.org/10.70675/5f1dee56z0ae7z4702zbd92z03596274e8f9openalex-snapshot
Computer-aided drug design of broad-spectrum antiviral compounds
inferred← citeshttps://doi.org/10.70675/ab76b9fcze4cbz45a3z950dz023b6506d0acopenalex-snapshot
Predictive models for kinetic and thermodynamic parameters of reactions
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