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Mold2, Molecular Descriptors from 2D Structures for Chemoinformatics and Toxicoinformatics
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Applying network analysis and Nebula (neighbor-edges based and unbiased leverage algorithm) to ToxCast data
inferred← citeshttps://doi.org/10.1016/j.fct.2017.08.028openalex-snapshot
Molecular dynamics simulations and applications in computational toxicology and nanotoxicology
inferred← citeshttps://doi.org/10.1016/j.fct.2017.09.058openalex-snapshot
MouseTox: An online toxicity assessment tool for small molecules through Enalos Cloud platform
inferred← citeshttps://doi.org/10.1016/j.fuel.2024.133438openalex-snapshot
A Multimodal Learning Model based on a QSPR approach for the estimation of RON, MON and CN, for any C, H, O hydrocarbons
inferred← citeshttps://doi.org/10.1016/j.isci.2021.103052openalex-snapshot
Comprehensive strategies of machine-learning-based quantitative structure-activity relationship models
inferred← citeshttps://doi.org/10.1016/j.isci.2022.105677openalex-snapshot
Supervised chemical graph mining improves drug-induced liver injury prediction
inferred← citeshttps://doi.org/10.1016/j.jhazmat.2015.01.051openalex-snapshot
Assessment of the electronic structure and properties of trichothecene toxins using density functional theory
inferred← citeshttps://doi.org/10.1016/j.jics.2022.100672openalex-snapshot
Automated QSPR modeling and data curation of physicochemical properties using KNIME platform: Prediction of partition coefficients
inferred← citeshttps://doi.org/10.1016/j.jinorgbio.2025.112890openalex-snapshot
Online OCHEM multi-task model for solubility and lipophilicity prediction of platinum complexes
inferred← citeshttps://doi.org/10.1016/j.jmgm.2020.107751openalex-snapshot
QSAR models for the fumigant activity prediction of essential oils
inferred← citeshttps://doi.org/10.1016/j.jmgm.2025.109126openalex-snapshot
Novel two variable-QSPR analysis for authentication and typification of vegetable oils
inferred← citeshttps://doi.org/10.1016/j.jpha.2025.101411openalex-snapshot
Unveiling optimal molecular features for hERG insights with automatic machine learning
inferred← citeshttps://doi.org/10.1016/j.matdes.2023.112452openalex-snapshot
In silico nanotoxicology: The computational biology state of art for nanomaterial safety assessments
inferred← citeshttps://doi.org/10.1016/j.molliq.2020.112572openalex-snapshot
Prediction of the aqueous solubility of diverse compounds by 2D-QSPR
inferred← citeshttps://doi.org/10.1016/j.molliq.2022.118616openalex-snapshot
Benchmarking machine learning methods for modeling physical properties of ionic liquids
inferred← citeshttps://doi.org/10.1016/j.molliq.2023.123323openalex-snapshot
Predictive modeling of physicochemical properties and ionicity of ionic liquids for virtual screening of novel electrolytes
inferred← citeshttps://doi.org/10.1016/j.molliq.2025.128417openalex-snapshot
Machine learning prediction of NMR shifts for rare and transition metal complexes (45Sc, 49Ti, 89Y, 91Zr, 139La)
inferred← citeshttps://doi.org/10.1016/j.nexres.2026.102362openalex-snapshot
A comprehensive review of chemoinformatics: From molecular representation to data-driven design
inferred← citeshttps://doi.org/10.1016/j.rechem.2021.100256openalex-snapshot
QSAR predictions on antichagas fenarimols
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2021.148820openalex-snapshot
Predicting zebrafish (Danio rerio) embryo developmental toxicity through a non-conformational QSAR approach
inferred← citeshttps://doi.org/10.1016/j.slasd.2024.01.005openalex-snapshot
The openOCHEM consensus model is the best-performing open-source predictive model in the First EUOS/SLAS joint compound solubility challenge
inferred← citeshttps://doi.org/10.1016/j.solener.2021.09.056openalex-snapshot
Prediction of non-radiative voltage losses in organic solar cells using machine learning
inferred← citeshttps://doi.org/10.1016/j.taap.2009.08.022openalex-snapshot
In silico toxicology for the pharmaceutical sciences☆
inferred← citeshttps://doi.org/10.1016/j.taap.2013.03.010openalex-snapshot
In silico modeling to predict drug-induced phospholipidosis
inferred← citeshttps://doi.org/10.1016/j.tox.2025.154064openalex-snapshot
InterDIA: Interpretable prediction of drug-induced autoimmunity through ensemble machine learning approaches
inferred← citeshttps://doi.org/10.1016/j.tox.2025.154230openalex-snapshot
AI-based toxicity prediction models using ToxCast data: Current status and future directions for explainable models
inferred← citeshttps://doi.org/10.1016/j.yrtph.2023.105486openalex-snapshot
DeepAmes: A deep learning-powered Ames test predictive model with potential for regulatory application
inferred← citeshttps://doi.org/10.1016/s1574-1400(09)00505-2openalex-snapshot
Chapter 5 Recent Advances on in silico ADME Modeling
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.0c00040openalex-snapshot
Most Influential Physicochemical and In Vitro Assay Descriptors for Hepatotoxicity and Nephrotoxicity Prediction
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.0c00347openalex-snapshot
Quantitative Structure–Activity Relationship (QSAR) Model for the Severity Prediction of Drug-Induced Rhabdomyolysis by Using Random Forest
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.0c00373openalex-snapshot
Trade-off Predictivity and Explainability for Machine-Learning Powered Predictive Toxicology: An in-Depth Investigation with Tox21 Data Sets
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.0c00374openalex-snapshot
DeepDILI: Deep Learning-Powered Drug-Induced Liver Injury Prediction Using Model-Level Representation
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.4c00421openalex-snapshot
Consensus Modeling for Predicting Chemical Binding to Transthyretin as the Winning Solution of the Tox24 Challenge
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.4c00428openalex-snapshot
DICTrank Is a Reliable Dataset for Cardiotoxicity Prediction Using Machine Learning Methods
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.5b00358openalex-snapshot
Development and Validation of Decision Forest Model for Estrogen Receptor Binding Prediction of Chemicals Using Large Data Sets
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.5c00018openalex-snapshot
Consensus Modeling Strategies for Predicting Transthyretin Binding Affinity from Tox24 Challenge Data
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.5c00033openalex-snapshot
Machine Learning for Toxicity Prediction Using Chemical Structures: Pillars for Success in the Real World
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.5c00273openalex-snapshot
Which Modern AI Methods Provide Accurate Predictions of Toxicological End Points? Analysis of Tox24 Challenge Results
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.9b00227openalex-snapshot
An Overview of Machine Learning and Big Data for Drug Toxicity Evaluation
inferred← citeshttps://doi.org/10.1021/acs.iecr.5c01348openalex-snapshot
Hybrid Approach for Predicting Melting Points in Nonionic Eutectic Solvents Using Thermodynamics and Machine Learning
inferred← citeshttps://doi.org/10.1021/acs.jcim.0c00139openalex-snapshot
Development of a Nicotinic Acetylcholine Receptor nAChR α7 Binding Activity Prediction Model
inferred← citeshttps://doi.org/10.1021/acs.jcim.2c00765openalex-snapshot
Investigation of a Data Split Strategy Involving the Time Axis in Adverse Event Prediction Using Machine Learning
inferred← citeshttps://doi.org/10.1021/acs.jcim.3c01309openalex-snapshot
Molecular Gas-Phase Conformational Ensembles
inferred← citeshttps://doi.org/10.1021/acs.jcim.4c00718openalex-snapshot
Identification of Active Molecules against Thrombocytopenia through Machine Learning
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00130openalex-snapshot
Rule-Based Prediction Models of Cytochrome P450 Inhibition
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00238openalex-snapshot
Deep Learning for Drug-Induced Liver Injury
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00663openalex-snapshot
Exploiting Multiple Descriptor Sets in QSAR Studies
inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00719openalex-snapshot
Integrating Drug’s Mode of Action into Quantitative Structure–Activity Relationships for Improved Prediction of Drug-Induced Liver Injury
inferred← citeshttps://doi.org/10.1021/acs.jcim.6c00414openalex-snapshot
Integrating QSAR-Machine Learning, Biochemical Assays, and Molecular Dynamics for the Discovery of JAK2 Inhibitors in Cervical Cancer
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00629openalex-snapshot
MuLiMs-MCoMPAs: A Novel Multiplatform Framework to Compute Tensor Algebra-Based Three-Dimensional Protein Descriptors
inferred← citeshttps://doi.org/10.1021/acs.jctc.3c01420openalex-snapshot
PointGAT: A Quantum Chemical Property Prediction Model Integrating Graph Attention and 3D Geometry
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.8b01048openalex-snapshot
Virtual Chemical Libraries
inferred← citeshttps://doi.org/10.1021/acsomega.4c02157openalex-snapshot
Interpretable AI and Machine Learning Classification for Identifying High-Efficiency Donor–Acceptor Pairs in Organic Solar Cells
inferred← citeshttps://doi.org/10.1021/acsomega.4c05768openalex-snapshot
Application of Machine Learning in the Development of Fourth Degree Quantitative Structure–Activity Relationship Model for Triclosan Analogs Tested against Plasmodium falciparum 3D7
inferred← citeshttps://doi.org/10.1021/acsptsci.3c00078openalex-snapshot
Rigid Scaffolds Are Promising for Designing Macrocyclic Kinase Inhibitors
inferred← citeshttps://doi.org/10.1021/ci400369zopenalex-snapshot
Visually Interpretable Models of Kinase Selectivity Related Features Derived from Field-Based Proteochemometrics
inferred← citeshttps://doi.org/10.1021/tx2000637openalex-snapshot
Comparative Analysis of Predictive Models for Nongenotoxic Hepatocarcinogenicity Using Both Toxicogenomics and Quantitative Structure–Activity Relationships
inferred← citeshttps://doi.org/10.1038/s41598-017-08793-2openalex-snapshot
Theoretical Studies of Intracellular Concentration of Micro-organisms’ Metabolites
inferred← citeshttps://doi.org/10.1038/s41598-017-17701-7openalex-snapshot
Development of Decision Forest Models for Prediction of Drug-Induced Liver Injury in Humans Using A Large Set of FDA-approved Drugs
inferred← citeshttps://doi.org/10.1038/s41598-021-93070-6openalex-snapshot
Random forest classification for predicting lifespan-extending chemical compounds
inferred← citeshttps://doi.org/10.1038/s41598-025-31230-8openalex-snapshot
In silico-driven identification of potent CDK9 inhibitors through bioisosteric replacement and multi-stage virtual screening
inferred← citeshttps://doi.org/10.1038/s42256-020-0209-yopenalex-snapshot
Minimal-uncertainty prediction of general drug-likeness based on Bayesian neural networks
inferred← citeshttps://doi.org/10.1038/srep32115openalex-snapshot
sNebula, a network-based algorithm to predict binding between human leukocyte antigens and peptides
inferred← citeshttps://doi.org/10.1039/9781837070206-00462openalex-snapshot
Machine Learning in Drug-induced Adverse Reaction Modeling: Case Studies of Drug-induced Cardiotoxicity Modeling
inferred← citeshttps://doi.org/10.1039/b917766copenalex-snapshot
A collaborative database and computational models for tuberculosis drug discovery
inferred← citeshttps://doi.org/10.1039/bk9781849730044-00148openalex-snapshot
Molecular Descriptors from Two-Dimensional Chemical Structure
inferred← citeshttps://doi.org/10.1039/c4md00216dopenalex-snapshot
Polypharmacology modelling using proteochemometrics (PCM): recent methodological developments, applications to target families, and future prospects
inferred← citeshttps://doi.org/10.1039/c4np00068dopenalex-snapshot
Chemo- and bioinformatics resources for in silico drug discovery from medicinal plants beyond their traditional use: a critical review
inferred← citeshttps://doi.org/10.1039/c4ra07756copenalex-snapshot
Enalos InSilicoNano platform: an online decision support tool for the design and virtual screening of nanoparticles
inferred← citeshttps://doi.org/10.1039/c5mb00036jopenalex-snapshot
Revealing the binding mode between respiratory syncytial virus fusion protein and benzimidazole-based inhibitors
inferred← citeshttps://doi.org/10.1039/c5mb00325copenalex-snapshot
Experimental and computational studies of fatty acid distribution networks
inferred← citeshttps://doi.org/10.1039/c5md00556fopenalex-snapshot
Predictive proteochemometric models for kinases derived from 3D protein field-based descriptors
inferred← citeshttps://doi.org/10.1039/c8na00142aopenalex-snapshot
A safe-by-design tool for functionalised nanomaterials through the Enalos Nanoinformatics Cloud platform
inferred← citeshttps://doi.org/10.1039/d0an00198hopenalex-snapshot
Metabolite collision cross section prediction without energy-minimized structures
inferred← citeshttps://doi.org/10.1039/d0ee02838jopenalex-snapshot
Machine learning for high performance organic solar cells: current scenario and future prospects
inferred← citeshttps://doi.org/10.1039/d1sc01000jopenalex-snapshot
A review on machine learning algorithms for the ionic liquid chemical space
inferred← citeshttps://doi.org/10.1039/d5cs00053jopenalex-snapshot
Accelerating battery innovation: AI-powered molecular discovery
inferred← citeshttps://doi.org/10.1039/d6ra05786aopenalex-snapshot
From QSAR to deep learning: an interpretable comprehensive pipeline with a read-across approach for mutagenicity prediction via the Enalos Cloud Platform
inferred← citeshttps://doi.org/10.1063/5.0123091openalex-snapshot
Artificial intelligence: Evolving role in drug design
inferred← citeshttps://doi.org/10.1080/00498254.2018.1527049openalex-snapshot
QSPR modelling of in vitro degradation half-life of acyl glucuronides
inferred← citeshttps://doi.org/10.1080/0305215x.2025.2464861openalex-snapshot
A multi-objective evolutionary algorithm for solving the feature selection problem of high-dimensional sparse data and its application in the absorption, distribution, metabolism, excretion and toxicity (ADMET) classification
inferred← citeshttps://doi.org/10.1080/07391102.2024.2326671openalex-snapshot
ANN multi-layer perceptron for prediction of blood–brain barrier permeable compounds for central nervous system therapeutics
inferred← citeshttps://doi.org/10.1080/10590501.2018.1537132openalex-snapshot
Computational prediction models for assessing endocrine disrupting potential of chemicals
inferred← citeshttps://doi.org/10.1080/10590501.2018.1537155openalex-snapshot
Machine learning models for predicting endocrine disruption potential of environmental chemicals
inferred← citeshttps://doi.org/10.1080/10629360903438370openalex-snapshot
QNA-based ‘Star Track’ QSAR approach
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/10.1080/1062936x.2017.1377765openalex-snapshot
Predicting the bioconcentration factor through a conformation-independent QSPR study
inferred← citeshttps://doi.org/10.1080/1062936x.2021.1905711openalex-snapshot
QSAR models for insecticidal properties of plant essential oils on the housefly (Musca domestica L.)
inferred← citeshttps://doi.org/10.1080/1062936x.2023.2232992openalex-snapshot
Design and experimental validation of the oxazole and thiazole derivatives as potential antivirals against of human cytomegalovirus
inferred← citeshttps://doi.org/10.1080/1062936x.2024.2394497openalex-snapshot
Quantitative structure-insecticidal activity of essential oils on the human head louse ( Pediculus humanus capitis )
inferred← citeshttps://doi.org/10.1080/15563650.2017.1333123openalex-snapshot
Hepatotoxicity evaluation of traditional Chinese medicines using a computational molecular model
inferred← citeshttps://doi.org/10.1080/17425255.2024.2377593openalex-snapshot
Machine learning and deep learning approaches for enhanced prediction of hERG blockade: a comprehensive QSAR modeling study
inferred← citeshttps://doi.org/10.1080/17460441.2023.2250721openalex-snapshot
Deep learning tools to accelerate antibiotic discovery
inferred← citeshttps://doi.org/10.1080/17474124.2018.1383154openalex-snapshot
The Liver Toxicity Knowledge Base (LKTB) and drug-induced liver injury (DILI) classification for assessment of human liver injury
inferred← citeshttps://doi.org/10.1080/26896583.2024.2396731openalex-snapshot
Unlocking the potential of AI: Machine learning and deep learning models for predicting carcinogenicity of chemicals
inferred← citeshttps://doi.org/10.1088/2632-2153/acb900openalex-snapshot
Quantum machine learning framework for virtual screening in drug discovery: a prospective quantum advantage
inferred← citeshttps://doi.org/10.1093/bib/bbaa160openalex-snapshot
Current development of integrated web servers for preclinical safety and pharmacokinetics assessments in drug development
inferred← citeshttps://doi.org/10.1093/bib/bbaa218openalex-snapshot
QSIdb: quorum sensing interference molecules
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