New Approach Combining Molecular Fingerprints and Machine Learning to Estimate Relative Ionization Efficiency in Electrospray Ionization
Alfred W. Mayhew, David Topping, Jacqueline F. Hamilton
Abstract
score of 0.62 and a root-mean-square error (RMSE) of 0.362. Such scores are comparable to those obtained in previous studies but without the requirement to first measure or predict the physical properties of the compounds, potentially reducing the time required to make predictions.
Topics & Concepts
Electrospray ionizationIonizationMetric (unit)Regression analysisMean squared errorRange (aeronautics)RegressionChemistryMass spectrometryCorrelation coefficientComputer scienceBiological systemArtificial intelligencePattern recognition (psychology)StatisticsMachine learningMathematicsChromatographyMaterials scienceIonEngineeringComposite materialOperations managementOrganic chemistryBiologyAnalytical Chemistry and ChromatographyMass Spectrometry Techniques and ApplicationsAdvanced Chemical Sensor Technologies