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-Reference-Cited by-同舟云学术

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

Published:2022-03-31 Issue:8 Volume:62 Page:1849-1862
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Molina Christophe¹^ORCID,Ait-Ouarab Lilia²,Minoux Hervé³

Affiliation:

1. PIKAÏROS S.A., B03 - 2 Allée de la Clairière, 31650 Saint Orens de Gameville, France

2. AMOA Ingénierie, INFOGENE S.A., 19, rue d’Orleans, 92200 Neuilly-sur-Seine, France

3. Data and Data Science, SANOFI R&D, 91380 Chilly-Mazarin, France

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.2c00293

Reference41 articles.

1. SCAM Detective: Accurate Predictor of Small, Colloidally Aggregating Molecules

2. Stoichiometry and Physical Chemistry of Promiscuous Aggregate-Based Inhibitors

3. Hit Dexter: A Machine-Learning Model for the Prediction of Frequent Hitters

4. Complementarity Between a Docking and a High-Throughput Screen in Discovering New Cruzain Inhibitors

5. Comprehensive Mechanistic Analysis of Hits from High-Throughput and Docking Screens against β-Lactamase

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