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Arkaprava Banerjee

Showing results (1-10 of 28) with videos related to

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Scientific Reports|September 6, 2024
The application of chemical similarity measures in an unconventional modeling framework c-RASAR along with dimensionality reduction techniques to a representative hepatotoxicity datasetArkaprava Banerjee, Kunal Roy
Methods in Molecular Biology (Clifton, N.J.)|September 23, 2024
Molecular Similarity in Predictive Toxicology with a Focus on the q-RASAR TechniqueArkaprava Banerjee, Kunal Roy
Expert Opinion on Drug Discovery|July 5, 2024
How to correctly develop q-RASAR models for predictive cheminformaticsArkaprava Banerjee, Kunal Roy
Molecular Diversity|June 29, 2022
First report of q-RASAR modeling toward an approach of easy interpretability and efficient transferabilityArkaprava Banerjee, Kunal Roy
Chemical Research in Toxicology|February 22, 2023
On Some Novel Similarity-Based Functions Used in the ML-Based q-RASAR Approach for Efficient Quantitative Predictions of Selected Toxicity End PointsArkaprava Banerjee, Kunal Roy
Scientific Reports|January 4, 2025
Machine learning assisted classification RASAR modeling for the nephrotoxicity potential of a curated set of orally active drugsArkaprava Banerjee, Kunal Roy
Chemical Research in Toxicology|August 16, 2023
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 CoefficientsArkaprava Banerjee, Kunal Roy
Journal of Hazardous Materials|July 25, 2025
A new approach methodology (NAM) for carcinogenicity prediction of organic chemicals using the multiclass ARKA framework and machine-learning-based stacking regressionArkaprava Banerjee, Kunal Roy
Environmental Science. Processes & Impacts|May 14, 2024
ARKA: a framework of dimensionality reduction for machine-learning classification modeling, risk assessment, and data gap-filling of sparse environmental toxicity dataArkaprava Banerjee, Kunal Roy
Environmental Science. Processes & Impacts|September 8, 2023
Read-across-based intelligent learning: development of a global q-RASAR model for the efficient quantitative predictions of skin sensitization potential of diverse organic chemicalsArkaprava Banerjee, Kunal Roy
Pageof 3

Showing results (1-10 of 28) with videos related to

Sort By:
Pageof 3
Scientific Reports|September 6, 2024
The application of chemical similarity measures in an unconventional modeling framework c-RASAR along with dimensionality reduction techniques to a representative hepatotoxicity datasetArkaprava Banerjee, Kunal Roy
Methods in Molecular Biology (Clifton, N.J.)|September 23, 2024
Molecular Similarity in Predictive Toxicology with a Focus on the q-RASAR TechniqueArkaprava Banerjee, Kunal Roy
Expert Opinion on Drug Discovery|July 5, 2024
How to correctly develop q-RASAR models for predictive cheminformaticsArkaprava Banerjee, Kunal Roy
Molecular Diversity|June 29, 2022
First report of q-RASAR modeling toward an approach of easy interpretability and efficient transferabilityArkaprava Banerjee, Kunal Roy
Chemical Research in Toxicology|February 22, 2023
On Some Novel Similarity-Based Functions Used in the ML-Based q-RASAR Approach for Efficient Quantitative Predictions of Selected Toxicity End PointsArkaprava Banerjee, Kunal Roy
Scientific Reports|January 4, 2025
Machine learning assisted classification RASAR modeling for the nephrotoxicity potential of a curated set of orally active drugsArkaprava Banerjee, Kunal Roy
Chemical Research in Toxicology|August 16, 2023
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 CoefficientsArkaprava Banerjee, Kunal Roy
Journal of Hazardous Materials|July 25, 2025
A new approach methodology (NAM) for carcinogenicity prediction of organic chemicals using the multiclass ARKA framework and machine-learning-based stacking regressionArkaprava Banerjee, Kunal Roy
Environmental Science. Processes & Impacts|May 14, 2024
ARKA: a framework of dimensionality reduction for machine-learning classification modeling, risk assessment, and data gap-filling of sparse environmental toxicity dataArkaprava Banerjee, Kunal Roy
Environmental Science. Processes & Impacts|September 8, 2023
Read-across-based intelligent learning: development of a global q-RASAR model for the efficient quantitative predictions of skin sensitization potential of diverse organic chemicalsArkaprava Banerjee, Kunal Roy
Pageof 3