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1.
Breaking the Barriers: Machine-Learning-Based c-RASAR Approach for Accurate Blood-Brain Barrier Permeability Prediction.
J Chem Inf Model
; 64(10): 4298-4309, 2024 May 27.
Artículo
en Inglés
| MEDLINE | ID: mdl-38700741
2.
On Some Novel Similarity-Based Functions Used in the ML-Based q-RASAR Approach for Efficient Quantitative Predictions of Selected Toxicity End Points.
Chem Res Toxicol
; 36(3): 446-464, 2023 03 20.
Artículo
en Inglés
| MEDLINE | ID: mdl-36811528
3.
Prediction-Inspired Intelligent Training for the Development of Classification Read-across Structure-Activity Relationship (c-RASAR) Models for Organic Skin Sensitizers: Assessment of Classification Error Rate from Novel Similarity Coefficients.
Chem Res Toxicol
; 36(9): 1518-1531, 2023 09 18.
Artículo
en Inglés
| MEDLINE | ID: mdl-37584642
4.
First report of q-RASAR modeling toward an approach of easy interpretability and efficient transferability.
Mol Divers
; 26(5): 2847-2862, 2022 Oct.
Artículo
en Inglés
| MEDLINE | ID: mdl-35767129
5.
ARKA: a framework of dimensionality reduction for machine-learning classification modeling, risk assessment, and data gap-filling of sparse environmental toxicity data.
Environ Sci Process Impacts
; 26(6): 991-1007, 2024 Jun 19.
Artículo
en Inglés
| MEDLINE | ID: mdl-38743054
6.
Application of machine learning-based read-across structure-property relationship (RASPR) as a new tool for predictive modelling: Prediction of power conversion efficiency (PCE) for selected classes of organic dyes in dye-sensitized solar cells (DSSCs).
Mol Inform
; 43(4): e202300210, 2024 Apr.
Artículo
en Inglés
| MEDLINE | ID: mdl-38374528
7.
Read-across-based intelligent learning: development of a global q-RASAR model for the efficient quantitative predictions of skin sensitization potential of diverse organic chemicals.
Environ Sci Process Impacts
; 25(10): 1626-1644, 2023 Oct 18.
Artículo
en Inglés
| MEDLINE | ID: mdl-37682520
8.
A machine learning q-RASPR approach for efficient predictions of the specific surface area of perovskites.
Mol Inform
; 42(4): e2200261, 2023 04.
Artículo
en Inglés
| MEDLINE | ID: mdl-36618002
9.
Efficient predictions of cytotoxicity of TiO2-based multi-component nanoparticles using a machine learning-based q-RASAR approach.
Nanotoxicology
; 17(1): 78-93, 2023 02.
Artículo
en Inglés
| MEDLINE | ID: mdl-36891579
10.
Machine learning - based q-RASAR modeling to predict acute contact toxicity of binary organic pesticide mixtures in honey bees.
J Hazard Mater
; 460: 132358, 2023 10 15.
Artículo
en Inglés
| MEDLINE | ID: mdl-37634379
11.
Quick and efficient quantitative predictions of androgen receptor binding affinity for screening Endocrine Disruptor Chemicals using 2D-QSAR and Chemical Read-Across.
Chemosphere
; 309(Pt 1): 136579, 2022 Dec.
Artículo
en Inglés
| MEDLINE | ID: mdl-36174732
12.
How to correctly develop q-RASAR models for predictive cheminformatics.
Expert Opin Drug Discov
; : 1-6, 2024 Jul 05.
Artículo
en Inglés
| MEDLINE | ID: mdl-38966910
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