Efficient predictions of cytotoxicity of TiO2-based multi-component nanoparticles using a machine learning-based q-RASAR approach
Author:
Affiliation:
1. Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
2. Chemometrics & Molecular Modeling Laboratory, Department of Chemistry, Kean University, Union, NJ, USA
Funder
Life Science Research Board, DRDO, New Delhi, India
Publisher
Informa UK Limited
Subject
Toxicology,Biomedical Engineering
Link
https://www.tandfonline.com/doi/pdf/10.1080/17435390.2023.2186280
Reference33 articles.
1. PLGA nanoparticles containing various anticancer agents and tumour delivery by EPR effect
2. Quantitative predictions from chemical read-across and their confidence measures
3. Quick and efficient quantitative predictions of androgen receptor binding affinity for screening Endocrine Disruptor Chemicals using 2D-QSAR and Chemical Read-Across
4. First report of q-RASAR modeling toward an approach of easy interpretability and efficient transferability
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