These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Random Forest Approach to QSPR Study of Fluorescence Properties Combining Quantum Chemical Descriptors and Solvent Conditions.
    Author: Chen CH, Tanaka K, Funatsu K.
    Journal: J Fluoresc; 2018 Mar; 28(2):695-706. PubMed ID: 29680928.
    Abstract:
    The Quantitative Structure - Property Relationship (QSPR) approach was performed to study the fluorescence absorption wavelengths and emission wavelengths of 413 fluorescent dyes in different solvent conditions. The dyes included the chromophore derivatives of cyanine, xanthene, coumarin, pyrene, naphthalene, anthracene and etc., with the wavelength ranging from 250 nm to 800 nm. An ensemble method, random forest (RF), was employed to construct nonlinear prediction models compared with the results of linear partial least squares and nonlinear support vector machine regression models. Quantum chemical descriptors derived from density functional theory method and solvent information were also used by constructing models. The best prediction results were obtained from RF model, with the squared correlation coefficients [Formula: see text] of 0.940 and 0.905 for λabs and λem, respectively. The descriptors used in the models were discussed in detail in this report by comparing the feature importance of RF.
    [Abstract] [Full Text] [Related] [New Search]