☰
−4−3−2−101234−4−2024
ENMGNP001GNP002GNP003GNP004GNP005GNP006GNP007GNP008GNP009GNP010GNP011GNP012GNP013GNP014GNP015GNP016GNP017GNP018GNP019GNP020GNP021GNP022GNP023GNP024GNP025GNP026GNP027GNP028GNP029GNP030GNP031GNP032GNP033GNP034GNP035GNP036GNP037GNP038GNP039GNP040GNP059GNP060GNP061GNP062GNP063GNP064GNP065GNP067GNP068GNP069GNP070GNP071GNP072GNP073GNP075GNP076GNP077GNP078GNP079GNP080GNP081GNP083GNP084GNP085GNP086GNP087GNP088GNP089GNP091GNP092GNP093GNP094GNP095GNP096GNP097GNP099GNP100GNP101GNP102GNP103GNP104GNP105GNP123GNP124GNP125GNP126GNP127GNP128GNP129GNP130GNP131GNP132GNP133GNP134GNP135GNP136GNP137GNP138GNP139GNP140GNP141GNP142GNP143GNP144GNP145GNP146GNP147GNP148GNP149PtNP001PtNP002PtNP003PtNP004PtNP005PtNP006PtNP007PtNP008PtNP009PtNP010PtNP011PdNP001PdNP002PdNP003PdNP004PdNP005PdNP006PdNP007PdNP008PdNP009PdNP010PdNP011Model for Nanomaterials with NanoAID-9ExperimentPrediction

1. Model Data

2. Model Deployment for Prediction

    Download File Example

3. Model Description

This is a partial least squares regression (PLSR) model for NanoAID-9 (logP).
The model was developed using a training set of 131 nanomaterials (NMs) and employed a 5-fold cross-validation procedure. Additionally, it was validated with a validation set of 16 NMs. The model's coefficient of determination (R2) for the training set is 0.673, and it has a root mean squared error (RMSE) of 0.905. For the validation set, the R2 value is 0.739, with an RMSE of 1.021. The experimental logP values of all the nanoparticles were determined using "shaking flask" method.