122 related articles for article (PubMed ID: 38705560)
1. Quantitative read-across structure-activity relationship (q-RASAR): A novel approach to estimate the subchronic oral safety (NOAEL) of diverse organic chemicals in rats.
Ghosh S; Roy K
Toxicology; 2024 Jun; 505():153824. PubMed ID: 38705560
[TBL] [Abstract][Full Text] [Related]
2. Quantitative Read-across structure-activity relationship (q-RASAR): A new approach methodology to model aquatic toxicity of organic pesticides against different fish species.
Ghosh S; Chatterjee M; Roy K
Aquat Toxicol; 2023 Dec; 265():106776. PubMed ID: 38006764
[TBL] [Abstract][Full Text] [Related]
3. Predictive Quantitative Read-Across Structure-Property Relationship Modeling of the Retention Time (Log
Ghosh S; Chatterjee M; Roy K
J Agric Food Chem; 2023 Jun; 71(24):9538-9548. PubMed ID: 37294004
[TBL] [Abstract][Full Text] [Related]
4. Machine learning - based q-RASAR modeling to predict acute contact toxicity of binary organic pesticide mixtures in honey bees.
Chatterjee M; Banerjee A; Tosi S; Carnesecchi E; Benfenati E; Roy K
J Hazard Mater; 2023 Oct; 460():132358. PubMed ID: 37634379
[TBL] [Abstract][Full Text] [Related]
5. On Some Novel Similarity-Based Functions Used in the ML-Based q-RASAR Approach for Efficient Quantitative Predictions of Selected Toxicity End Points.
Banerjee A; Roy K
Chem Res Toxicol; 2023 Mar; 36(3):446-464. PubMed ID: 36811528
[TBL] [Abstract][Full Text] [Related]
6. 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.
Banerjee A; Roy K
Chem Res Toxicol; 2023 Sep; 36(9):1518-1531. PubMed ID: 37584642
[TBL] [Abstract][Full Text] [Related]
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.
Banerjee A; Roy K
Environ Sci Process Impacts; 2023 Oct; 25(10):1626-1644. PubMed ID: 37682520
[TBL] [Abstract][Full Text] [Related]
8. First report of q-RASAR modeling toward an approach of easy interpretability and efficient transferability.
Banerjee A; Roy K
Mol Divers; 2022 Oct; 26(5):2847-2862. PubMed ID: 35767129
[TBL] [Abstract][Full Text] [Related]
9. Efficient predictions of cytotoxicity of TiO
Banerjee A; Kar S; Pore S; Roy K
Nanotoxicology; 2023 Feb; 17(1):78-93. PubMed ID: 36891579
[TBL] [Abstract][Full Text] [Related]
10. Unveiling first report on in silico modeling of aquatic toxicity of organic chemicals to Labeo rohita (Rohu) employing QSAR and q-RASAR.
Gallagher A; Kar S
Chemosphere; 2024 Feb; 349():140810. PubMed ID: 38029938
[TBL] [Abstract][Full Text] [Related]
11. Integrated predictive QSAR, Read Across, and q-RASAR analysis for diverse agrochemical phytotoxicity in oat and corn: A consensus-based approach for risk assessment and prioritization.
Pandey NK; Murmu A; Banjare P; Matore BW; Singh J; Roy PP
Environ Sci Pollut Res Int; 2024 Feb; 31(8):12371-12386. PubMed ID: 38228952
[TBL] [Abstract][Full Text] [Related]
12. 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).
Pore S; Banerjee A; Roy K
Mol Inform; 2024 Apr; 43(4):e202300210. PubMed ID: 38374528
[TBL] [Abstract][Full Text] [Related]
13. Prediction of acute toxicity for Chlorella vulgaris caused by tire wear particle-derived compounds using quantitative structure-activity relationship models.
Jiang JR; Cai WX; Chen ZF; Liao XL; Cai Z
Water Res; 2024 Jun; 256():121643. PubMed ID: 38663211
[TBL] [Abstract][Full Text] [Related]
14. From molecular descriptors to the developmental toxicity prediction of pesticides/veterinary drugs/bio-pesticides against zebrafish embryo: Dual computational toxicological approaches for prioritization.
Wang Y; Wang P; Fan T; Ren T; Zhang N; Zhao L; Zhong R; Sun G
J Hazard Mater; 2024 Jun; 476():134945. PubMed ID: 38905984
[TBL] [Abstract][Full Text] [Related]
15. QSAR modeling of toxicity of diverse organic chemicals to Daphnia magna using 2D and 3D descriptors.
Kar S; Roy K
J Hazard Mater; 2010 May; 177(1-3):344-51. PubMed ID: 20045248
[TBL] [Abstract][Full Text] [Related]
16. First report on chemometric modeling of tilapia fish aquatic toxicity to organic chemicals: Toxicity data gap filling.
Yang S; Kar S
Sci Total Environ; 2024 Jan; 907():167991. PubMed ID: 37898216
[TBL] [Abstract][Full Text] [Related]
17. Ecotoxicological QSAR modeling of organic compounds against fish: Application of fragment based descriptors in feature analysis.
Khan K; Baderna D; Cappelli C; Toma C; Lombardo A; Roy K; Benfenati E
Aquat Toxicol; 2019 Jul; 212():162-174. PubMed ID: 31128417
[TBL] [Abstract][Full Text] [Related]
18. Quick and efficient quantitative predictions of androgen receptor binding affinity for screening Endocrine Disruptor Chemicals using 2D-QSAR and Chemical Read-Across.
Banerjee A; De P; Kumar V; Kar S; Roy K
Chemosphere; 2022 Dec; 309(Pt 1):136579. PubMed ID: 36174732
[TBL] [Abstract][Full Text] [Related]
19. q-RASTR modelling for prediction of diverse toxic chemicals towards
Ghosh V; Bhattacharjee A; Kumar A; Ojha PK
SAR QSAR Environ Res; 2024 Jan; 35(1):11-30. PubMed ID: 38193248
[TBL] [Abstract][Full Text] [Related]
20. Breaking the Barriers: Machine-Learning-Based c-RASAR Approach for Accurate Blood-Brain Barrier Permeability Prediction.
Kumar V; Banerjee A; Roy K
J Chem Inf Model; 2024 May; 64(10):4298-4309. PubMed ID: 38700741
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]