2020
DOI: 10.1039/d0ra05231k
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PLS and N-PLS based MIA-QSPR modeling of the photodegradation half-lives for polychlorinated biphenyl congeners

Abstract: Multivariate image analysis as a useful tool in environmental risk assessment studies.

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Cited by 2 publications
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“…To do this, a quantitative structure-property relationship (QSPR) analysis of the ability of pteridines to generate 1 O 2 was performed. QSPR and machine learning are used in photochemistry to offer fruitful results and allow for the prediction of the maximum absorption wavelength [ 210 , 211 , 212 ], fluorescence intensity [ 213 , 214 ], photoinduced toxicity, photolysis rate constant, photolysis half-life, and quantum yield [ 215 , 216 , 217 ]. In addition to pterins, the analyzed dataset included flavins and lumazine.…”
Section: Interactions Of Pterins With Metalsmentioning
confidence: 99%
“…To do this, a quantitative structure-property relationship (QSPR) analysis of the ability of pteridines to generate 1 O 2 was performed. QSPR and machine learning are used in photochemistry to offer fruitful results and allow for the prediction of the maximum absorption wavelength [ 210 , 211 , 212 ], fluorescence intensity [ 213 , 214 ], photoinduced toxicity, photolysis rate constant, photolysis half-life, and quantum yield [ 215 , 216 , 217 ]. In addition to pterins, the analyzed dataset included flavins and lumazine.…”
Section: Interactions Of Pterins With Metalsmentioning
confidence: 99%