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SAR and QSAR in Environmental Research Volume 33, 2022 - Issue 6
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Research Article

Carcinogenicity prediction using the index of ideality of correlation

A.P. ToropovaDepartment of Environmental Health Science, Laboratory of Environmental Chemistry and Toxicology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, ItalyCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-4194-9963View further author information
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A.A. ToropovDepartment of Environmental Health Science, Laboratory of Environmental Chemistry and Toxicology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, ItalyORCID Iconhttps://orcid.org/0000-0001-6864-6340View further author information
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E.L. ViganòDepartment of Environmental Health Science, Laboratory of Environmental Chemistry and Toxicology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, ItalyView further author information
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E. ColomboDepartment of Environmental Health Science, Laboratory of Environmental Chemistry and Toxicology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, ItalyView further author information
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A. RoncaglioniDepartment of Environmental Health Science, Laboratory of Environmental Chemistry and Toxicology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, ItalyORCID Iconhttps://orcid.org/0000-0002-1734-0939View further author information
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E. BenfenatiDepartment of Environmental Health Science, Laboratory of Environmental Chemistry and Toxicology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, ItalyORCID Iconhttps://orcid.org/0000-0002-3976-5989View further author information
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Pages 419-428 | Received 31 Mar 2022, Accepted 09 May 2022, Published online: 01 Jun 2022

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A.P. Toropova, A.A. Toropov, A. Roncaglioni & E. Benfenati. (2022) Monte Carlo technique to study the adsorption affinity of azo dyes by applying new statistical criteria of the predictive potential. SAR and QSAR in Environmental Research 33:8, pages 621-630.
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Articles from other publishers (1)

Parvin Kumar, Ashwani Kumar, Jayant Sindhu & Sohan Lal. (2023) Quasi-SMILES as a basis for the development of QSPR models to predict the CO2 capture capacity of deep eutectic solvents using correlation intensity index and consensus modelling. Fuel 345, pages 128237.
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