Literature DB >> 29680928

Random Forest Approach to QSPR Study of Fluorescence Properties Combining Quantum Chemical Descriptors and Solvent Conditions.

Chia-Hsiu Chen1, Kenichi Tanaka1, Kimito Funatsu2.   

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.

Entities:  

Keywords:  Fluorescence properties; QSPR; Quantum chemical calculation; Random forest

Year:  2018        PMID: 29680928     DOI: 10.1007/s10895-018-2233-4

Source DB:  PubMed          Journal:  J Fluoresc        ISSN: 1053-0509            Impact factor:   2.217


  13 in total

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Authors:  Florbela Pereira; Kaixia Xiao; Diogo A R S Latino; Chengcheng Wu; Qingyou Zhang; Joao Aires-de-Sousa
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Review 9.  Fluorescent sensors for measuring metal ions in living systems.

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Journal:  J Org Chem       Date:  2006-12-22       Impact factor: 4.354

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