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  • 1
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 4 (1990), S. 97-100 
    ISSN: 0886-9383
    Keywords: Matrix decomposition ; NIPALS ; Principal component ; SIMCA ; PLS ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The Non-linear Iterative Partial Least Squares (NIPALS) algorithm is used in principal component analysis to decompose a data matrix into score vectors and eigenvectors (loading vectors) plus a residual matrix. NIPALS starts with some guessed starting vector. The principal components obtained by NIPALS depends on the starting vector; the first principal component could not always be computed. Wold has suggested a starting vector for NIPALS, but we have found that even if this starting vector is used, the first principal component cannot be obtained in all cases. The reason why such a situation occurs is explained by the power method. A simple modification of the original NIPALS procedure to avoid getting smaller eigenvalues is presented.
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 0192-8651
    Keywords: Computational Chemistry and Molecular Modeling ; Biochemistry
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Computer Science
    Notes: Structure-taste relationships for 25 acyclic and 20 cyclic carbosulfamates were investigated by means of pattern recognition using different graph theoretical invariants as molecular substituent descriptors. The SIMCA method was used to classify the compounds into sweet and nonsweet classes. All selected graph theoretical invariants that are related to the “rooted” vertex were found to give promising results. Using the weighted path numbers and self-returning walks for the rooted atom as descriptors of substituents, we found 87% of acyclic compounds were correctly classified. Using the atomic path numbers for the rooted atom as descriptors of substituents, we found 81% of cyclic compounds were correctly classified. These results are better than previously used shape and size substituent descriptors. It may be concluded that the graph theoretical descriptors have great potential in encoding structure components in structure-activity studies (SAR) studies.
    Additional Material: 3 Ill.
    Type of Medium: Electronic Resource
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