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  • 1
    Electronic Resource
    Electronic Resource
    Statistical molecular design of peptoid libraries (1998)
    Springer
    Molecular diversity 4 (1998), S. 103-114 
    Details
    ISSN: 1573-501X
    Keywords: combinatorial chemistry ; D-optimal design ; PCA ; peptoid libraries ; PLS ; QSAR ; statistical molecular design
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Abstract Statistical experimental design provides an efficient approach for selecting the building blocks to span the structural space and increase the information content in a combinatorial library. A set of renin-inhibitors, hexapeptoids, is used to illustrate the approach. Multivariate quantitative structure-activity relationships (MQSARs) were developed relating renin inhibition to the peptoid sequences variation, parametrized by the z-scales. By using the information from the models, the number of building block sets could be reduced from six to three. Using a statistical molecular design (SMD) reduces the number of compounds from more than 100 000 down to 90. A second SMD was used for comparison, based on less prior knowledge. This gave a reduction from over 2 billion to 120 compounds.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1026416430656
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  • 2
    Electronic Resource
    Electronic Resource
    Relationships between higher-order data array configurations and problem formulations in multivariate data analysis (1989)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 3 (1989), S. 33-48 
    Details
    ISSN: 0886-9383
    Keywords: Higher-order data arrays ; Dimensionality ; Data modelling ; Classification ; Discrimination ; Correlation ; Regression ; Systematics of data analysis ; Opportunities for future developments ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: A scaffold for detailed understanding of the concept ‘dimensionality’ in data analysis is furnished by a systematic classification of higher-order data array configurations. Three major types of problem formulation in multivariate data analysis can be characterized for relevant data classes: 1data description (intra-class data structure modelling of inter-object and inter-variable relationships)2classification (inter-class discrimination)3correlation, regression (inter-variable relationships).The relationship between these three categories of data analytical problem formulation and the fundamental data array classification is exposed. These relations are augmented to include the general case of data arrays of order R, and R-way data analysis with the use of bilinear projections is presented. Based upon this, some possible directions for the future development of data analysis may be imagined.
    Additional Material: 8 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/cem.1180030106
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    Paper (German National Licenses)
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