Machine Learning Model for Screening Thyroid Stimulating Hormone Receptor Agonists Based on Updated Datasets and Improved Applicability Domain Metrics.
Sign Up to like & getrecommendations! Published in 2023 at "Chemical research in toxicology"
DOI: 10.1021/acs.chemrestox.3c00074
Abstract: Machine learning (ML) models for screening endocrine-disrupting chemicals (EDCs), such as thyroid stimulating hormone receptor (TSHR) agonists, are essential for sound management of chemicals. Previous models for screening TSHR agonists were built on imbalanced datasets… read more here.
Keywords: methodology; applicability domain; machine learning; hormone receptor ... See more keywords
Applicability Domain of Polyparameter Linear Free Energy Relationship Models Evaluated by Leverage and Prediction Interval Calculation
Sign Up to like & getrecommendations! Published in 2022 at "Environmental Science & Technology"
DOI: 10.1021/acs.est.2c00865
Abstract: Polyparameter linear free energy relationships (PP-LFERs) are accurate and robust models employed to predict equilibrium partition coefficients (K) of organic chemicals. The accuracy of predictions by a PP-LFER depends on the composition of the respective… read more here.
Keywords: prediction interval; polyparameter linear; applicability domain; leverage prediction ... See more keywords
Trustworthiness, the Key to Grid-Based Map-Driven Predictive Model Enhancement and Applicability Domain Control
Sign Up to like & getrecommendations! Published in 2020 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.0c00998
Abstract: In chemography, grid-based maps sample molecular descriptor space by injecting a set of nodes, and then linking them to some regular 2D grid representing the map. They include self-organizing maps (SOMs) and generative topographic maps… read more here.
Keywords: applicability domain; trustworthiness; based map; map driven ... See more keywords
Isometric Stratified Ensembles: A Partial and Incremental Adaptive Applicability Domain and Consensus-Based Classification Strategy for Highly Imbalanced Data Sets with Application to Colloidal Aggregation
Sign Up to like & getrecommendations! Published in 2022 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.2c00293
Abstract: Partial and incremental stratification analysis of a quantitative structure-interference relationship (QSIR) is a novel strategy intended to categorize classification provided by machine learning techniques. It is based on a 2D mapping of classification statistics onto… read more here.
Keywords: isometric stratified; applicability domain; classification; strategy ... See more keywords
A Distance-Based Boolean Applicability Domain for Classification of High Throughput Screening Data
Sign Up to like & getrecommendations! Published in 2019 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.8b00499
Abstract: In Quantitative Structure-Activity Relationship (QSAR) modeling, one must come up with an activity model but also with an applicability domain for that model. Some existing methods to create an applicability domain are complex, hard to… read more here.
Keywords: distance based; applicability domain; based boolean; applicability ... See more keywords