Prediction of Retention Time and Collision Cross Section (CCS H+ , CCS H– , and CCS Na+ ) of Emerging Contaminants Using Multiple Adaptive Regression Splines

Alberto Celma, Richard Bade, Juan V. Sancho, Félix Hernández, Melissa Humphries, Lubertus Bijlsma

2022Journal of Chemical Information and Modeling31 citationsDOI Open Access PDF

Abstract

= 0.954) with deviation below ±5.25% for 95% of the cases. The developed models have been incorporated in an open-access and user-friendly online platform which represents a great advantage for third-party research laboratories for predicting both RT and CCS data.

Topics & Concepts

UnivariateMars Exploration ProgramMultivariate adaptive regression splinesChemistryMultivariate statisticsData miningRegression analysisComputer scienceMachine learningBayesian multivariate linear regressionPhysicsAstronomyAnalytical Chemistry and ChromatographyMass Spectrometry Techniques and ApplicationsMetabolomics and Mass Spectrometry Studies

Prediction of Retention Time and Collision Cross Section (CCS <sub>H+</sub> , CCS <sub>H–</sub> , and CCS <sub>Na+</sub> ) of Emerging Contaminants Using Multiple Adaptive Regression Splines

Abstract

Topics & Concepts