What is it about?
New robust QSRR model is proposed to be an efficient tool to predict retention indices of essential oils components.
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Why is it important?
The modeling method is new in the prediction of the retention indices of essential oils. In addition, the proposed method was developed to be efficient based on the following steps: First, dimension reduction was performed using the proposed modified robust sure independence screening (MR-SIS) method. Second, prediction of RIs was made using the proposed robust sparse QSRR with smoothly clipped absolute deviation (SCAD) penalty.
Perspectives
This article is really a new and significant contribution with advanced progress to the essential oil area and prediction of the retention indices.
Abdo Al-Fakih
Universiti Teknologi Malaysia
Read the Original
This page is a summary of: A sparse QSRR model for predicting retention indices of essential oils based on robust screening approach, SAR and QSAR in Environmental Research, August 2017, Taylor & Francis,
DOI: 10.1080/1062936x.2017.1375010.
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