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Review of QSAR Models and Software Tools for predicting Developmental and Reproductive Toxicity
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Quantitative structure-activity relationships for the developmental toxicity of haloacetic acids in mammalian whole embryo culture
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‘Dynamic’ QSAR For Semicarbazide-induced Mortality in Frog Embryos
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Developmental toxicity of carboxylic acids to Xenopus embryos: A quantitative structure‐activity relationship and computer‐automated structure evaluation
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Teratogenesis: A statistical structure-activity model
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Challenges in constructing statistically based structure‐activity relationship models for developmental toxicity
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ChemInform Abstract: Probabilistic Approaches in Activity Prediction
inferredcites →https://doi.org/10.1002/qsar.200710118openalex-snapshot
(Q)SARs for Predicting Effects Relating to Reproductive Toxicity
inferredcites →https://doi.org/10.1002/qsar.200960011openalex-snapshot
Formation of Structural Categories to Allow for Read‐Across for Teratogenicity
inferredcites →https://doi.org/10.1002/tera.1420410106openalex-snapshot
Structure‐activity relationships in the developmental toxicity of substituted phenols: In vivo effects
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Additive incidence of developmental malformation for Xenopus embryos exposed to a mixture of ten aliphatic carboxylic acids
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Assessment of developmental toxicity potential of chemicals by quantitative structure-toxicity relationship models
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Initial evaluation of developmental malformation as an end point in mixture toxicity hazard assessment for aquatic vertebrates
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A qualitative assessment of developmental toxicity within a series of structurally related dopamine mimetics
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Structural basis for androgen receptor agonists and antagonists: Interaction of SPEED 98-listed chemicals and related compounds with the androgen receptor based on an in vitro reporter gene assay and 3D-QSAR
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QSAR of estrogen receptor modulators: exploring selectivity requirements for ERα versus ERβ binding of tetrahydroisoquinoline derivatives using E-state and physicochemical parameters
inferredcites →https://doi.org/10.1016/j.jmgm.2007.02.001openalex-snapshot
Structural and chemical basis for enhanced affinity and potency for a large series of estrogen receptor ligands: 2D and 3D QSAR studies
inferredcites →https://doi.org/10.1016/j.jmgm.2009.09.005openalex-snapshot
Pharmacophore and QSAR modeling of estrogen receptor β ligands and subsequent validation and in silico search for new hits
inferredcites →https://doi.org/10.1016/j.reprotox.2009.03.016openalex-snapshot
Profiling the activity of environmental chemicals in prenatal developmental toxicity studies using the U.S. EPA's ToxRefDB
inferredcites →https://doi.org/10.1016/j.reprotox.2009.12.003openalex-snapshot
Integrating (Q)SAR models, expert systems and read-across approaches for the prediction of developmental toxicity
inferredcites →https://doi.org/10.1016/j.yrtph.2006.10.001openalex-snapshot
A comprehensive model for reproductive and developmental toxicity hazard identification: II. Construction of QSAR models to predict activities of untested chemicals
inferredcites →https://doi.org/10.1016/j.yrtph.2006.11.002openalex-snapshot
A comprehensive model for reproductive and developmental toxicity hazard identification: I. Development of a weight of evidence QSAR database
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The challenge of reproductive and developmental toxicology under REACH
inferredcites →https://doi.org/10.1016/s0039-128x(96)00242-5openalex-snapshot
The estradiol pharmacophore: Ligand structure-estrogen receptor binding affinity relationships and a model for the receptor binding site
inferredcites →https://doi.org/10.1016/s0048-9697(99)00221-1openalex-snapshot
Specific binding of hydroxylated polychlorinated biphenyl metabolites and other substances to bovine calf uterine estrogen receptor: structure-binding relationships
inferredcites →https://doi.org/10.1016/s0166-1280(02)00625-5openalex-snapshot
Dynamic 3D QSAR techniques: applications in toxicology
inferredcites →https://doi.org/10.1016/s0166-1280(99)00360-7openalex-snapshot
Molecular fields in quantitative structure–permeation relationships: the VolSurf approach
inferredcites →https://doi.org/10.1021/ci050077copenalex-snapshot
MTD−PLS: A PLS Variant of the Minimal Topologic Difference Method. III. Mapping Interactions between Estradiol Derivatives and the Alpha Estrogenic Receptor
inferredcites →https://doi.org/10.1021/ci0501645openalex-snapshot
Variable Selection and Interpretation in Structure−Affinity Correlation Modeling of Estrogen Receptor Binders
inferredcites →https://doi.org/10.1021/ci800149wopenalex-snapshot
Computationally Identified Novel Diphenyl- and Phenylpyridine Androgen Receptor Antagonist Structures
inferredcites →https://doi.org/10.1021/ci8002182openalex-snapshot
Structure-Based Approach for the Study of Estrogen Receptor Binding Affinity and Subtype Selectivity
inferredcites →https://doi.org/10.1021/ci980335oopenalex-snapshot
Chemical Similarity Assessment through Multilevel Neighborhoods of Atoms: Definition and Comparison with the Other Descriptors
inferredcites →https://doi.org/10.1021/es049665hopenalex-snapshot
Consensus kNN QSAR: A Versatile Method for Predicting the Estrogenic Activity of Organic Compounds In Silico. A Comparative Study with Five Estrogen Receptors and a Large, Diverse Set of Ligands
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/jm000941mopenalex-snapshot
GRid-INdependent Descriptors (GRIND): A Novel Class of Alignment-Independent Three-Dimensional Molecular Descriptors
inferredcites →https://doi.org/10.1021/jm049687eopenalex-snapshot
Raptor: Combining Dual-Shell Representation, Induced-Fit Simulation, and Hydrophobicity Scoring in Receptor Modeling: Application toward the Simulation of Structurally Diverse Ligand Sets
inferredcites →https://doi.org/10.1021/jm050185qopenalex-snapshot
Combining Protein Modeling and 6D-QSAR. Simulating the Binding of Structurally Diverse Ligands to the Estrogen Receptor
inferredcites →https://doi.org/10.1021/jm050604jopenalex-snapshot
Identification of the Structural Requirements of the Receptor-Binding Affinity of Diphenolic Azoles to Estrogen Receptors α and β by Three-Dimensional Quantitative Structure−Activity Relationship and Structure−Activity Relationship Analysis
inferredcites →https://doi.org/10.1021/tx000208yopenalex-snapshot
Structure−Activity Relationships for a Large Diverse Set of Natural, Synthetic, and Environmental Estrogens
inferredcites →https://doi.org/10.1021/tx7002382openalex-snapshot
Screening of 397 Chemicals and Development of a Quantitative Structure−Activity Relationship Model for Androgen Receptor Antagonism
inferredcites →https://doi.org/10.1080/10408440600894914openalex-snapshot
A Category Approach for Reproductive Effects of Phthalates
inferredcites →https://doi.org/10.1080/1062936021000043445openalex-snapshot
PLS-QSAR of the adult and developmental toxicity of chemicals to Hydra attenuata
inferredcites →https://doi.org/10.1080/10629360290023377openalex-snapshot
QSAR modeling of the adult and developmental toxicity of glycols, glycol ethers and xylenes to hydra attenuata
inferredcites →https://doi.org/10.1080/1062936031000073126openalex-snapshot
Decision tree SAR models for developmental toxicity based on an FDA/TERIS database
inferredcites →https://doi.org/10.1080/10629360310001623953openalex-snapshot
In silicomodelling of hazard endpoints: current problems and perspectives
inferredcites →https://doi.org/10.1080/10629360310001623962openalex-snapshot
Comparative molecular field analysis (CoMFA) model using a large diverse set of natural, synthetic and environmental chemicals for binding to the androgen receptor
inferredcites →https://doi.org/10.1080/1062936032000101510openalex-snapshot
(Q)SAR S : gatekeepers against risk on chemicals?
inferredcites →https://doi.org/10.1080/1062936032000169633openalex-snapshot
The Utility of Structure–Activity Relationship (SAR) Models for Prediction and Covariate Selection in Developmental Toxicity: Comparative Analysis of Logistic Regression and Decision Tree Models
inferredcites →https://doi.org/10.1080/10629360412331319808openalex-snapshot
The Impact of variable selection on the modelling of oestrogenicity
inferredcites →https://doi.org/10.1080/10629360412331319826openalex-snapshot
In silicoprediction of receptor-mediated environmental toxic phenomena—application to endocrine disruption
inferredcites →https://doi.org/10.1080/10629360601053893openalex-snapshot
Structure-based modelling in reproductive toxicology: (Q)SARs for the placental barrier
inferredcites →https://doi.org/10.1080/10629360601053992openalex-snapshot
QSAR and mechanistic interpretation of estrogen receptor binding
inferredcites →https://doi.org/10.1080/10629360601054032openalex-snapshot
PASS: identification of probable targets and mechanisms of toxicity
inferredcites →https://doi.org/10.1080/10629360802550473openalex-snapshot
QSAR models for reproductive toxicity and endocrine disruption in regulatory use – a preliminary investigation
inferredcites →https://doi.org/10.1080/10659360500203022openalex-snapshot
Anin silicoensemble method for lead discovery: decision forest
inferredcites →https://doi.org/10.1080/10659360500204368openalex-snapshot
QSAR study of natural, synthetic and environmental endocrine disrupting compounds for binding to the androgen receptor
inferredcites →https://doi.org/10.1080/10659360500204442openalex-snapshot
Two-step models to predict binding affinity of chemicals to the human estrogen receptor α by three-dimensional quantitative structure–activity relationships (3D-QSARs) using receptor-ligand docking simulation
inferredcites →https://doi.org/10.1080/10659360600636022openalex-snapshot
Prediction of estrogenicity: validation of a classification model
inferredcites →https://doi.org/10.1093/emboj/18.17.4608openalex-snapshot
Structure of the ligand‐binding domain of oestrogen receptor beta in the presence of a partial agonist and a full antagonist
inferredcites →https://doi.org/10.1093/toxsci/kfl103openalex-snapshot
The ToxCast Program for Prioritizing Toxicity Testing of Environmental Chemicals
inferredcites →https://doi.org/10.1093/toxsci/kfp080openalex-snapshot
Profiling the Reproductive Toxicity of Chemicals from Multigeneration Studies in the Toxicity Reference Database
inferredcites →https://doi.org/10.1177/026119290903700506openalex-snapshot
In Silico Toxicology in Drug Discovery — Concepts Based on Three-dimensional Models
inferredcites →https://doi.org/10.1248/bpb.31.1453openalex-snapshot
Molecular Design Based on Receptor-Independent Pharmacophore: Application to Estrogen Receptor Ligands
inferredcites →https://doi.org/10.1289/txg.7125openalex-snapshot
Assessment of Prediction Confidence and Domain Extrapolation of Two Structure–Activity Relationship Models for Predicting Estrogen Receptor Binding Activity
inferredcites →https://doi.org/10.1351/pac200375112389openalex-snapshot
QSAR prioritization of chemical inventories for endocrine disruptor testing
inferredcites →https://doi.org/10.14573/altex.2009.3.167openalex-snapshot
VirtualToxLab™ - In silico prediction of the toxic (endocrine-disrupting) potential of drugs, chemicals and natural products. Two years and 2,000 compounds of experience: a progress report
inferredcites →https://doi.org/10.1897/05-367r.1openalex-snapshot
Comparison of the applicability domain of a quantitative structure-activity relationship for estrogenicity with a large chemical inventory
inferredcites →https://doi.org/10.2174/138920008786049294openalex-snapshot
The Use of Metabolising Systems for In Vitro Testing of Endocrine Disruptors
inferredcites →https://doi.org/10.2174/1568026013395074openalex-snapshot
Integration of Computational Analysis as a Sentinel Tool in Toxicological Assessments
inferredcites →https://doi.org/10.3109/00498258909043197openalex-snapshot
Teratogenicity of phenylhydantoins in an in vitro system: Molecular orbital-generated quantitative structure-toxicity relationships
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Zebrafish AC modelling: (Q)SAR models to predict developmental toxicity in zebrafish embryo
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