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A General Treatment of Solubility. 3. Principal Component Analysis (PCA) of the Solubilities of Diverse Solutes in Diverse Solvents
- Source :
- Journal of Chemical Information and Modeling. 45:913-923
- Publication Year :
- 2005
- Publisher :
- American Chemical Society (ACS), 2005.
-
Abstract
- A phenomenological study of solubility has been conducted using a combination of quantitative structure-property relationship (QSPR) and principal component analysis (PCA). A solubility database of 4540 experimental data points was used that utilized available experimental data into a matrix of 154 solvents times 397 solutes. Methodology in which QSPR and PCA are combined was developed to predict the missing values and to fill the data matrix. PCA on the resulting filled matrix, where solutes are observations and solvents are variables, shows 92.55% of coverage with three principal components. The corresponding transposed matrix, in which solvents are observations and solutes are variables, showed 62.96% of coverage with four principal components.
- Subjects :
- Quantitative structure–activity relationship
Chromatography
Chemistry
General Chemical Engineering
Thermodynamics
General Chemistry
Library and Information Sciences
Missing data
Data matrix (multivariate statistics)
Computer Science Applications
Matrix (chemical analysis)
Quantitative Structure Property Relationship
Principal component analysis
Which solvents
Solubility
Subjects
Details
- ISSN :
- 1549960X and 15499596
- Volume :
- 45
- Database :
- OpenAIRE
- Journal :
- Journal of Chemical Information and Modeling
- Accession number :
- edsair.doi.dedup.....6193b91dee46c9e0feb74c53166a4e7e
- Full Text :
- https://doi.org/10.1021/ci0496189