Three-Block Bi-Focal PLS (3BIF-PLS) and its Application in QSAR.
| Authors | |
|---|---|
| Year of publication | 2004 |
| Type | Article in Periodical |
| Magazine / Source | SAR and QSAR in Environmental Research |
| MU Faculty or unit | |
| Citation | |
| Web | http://ncbr.chemi.muni.cz/~jiri/pdf/sarqsar04.pdf |
| Field | Applied statistics, operation research |
| Keywords | Sphingomonas paucimobilis UT26;haloalkane dehalogenase; three-block bi-focal PLS;"DNA-fingerprinting" technology |
| Description | When X and Y are multivariate the two-block partial least squares (PLS) method is often used. In this paper we outline an extension addressing a special case of the three-block (X/Y/Z) problem, where Z sits "under" Y. We call this approach 3BIF-PLS. It views the X/Y relationship as the dominant problem, and seeks to use the additional information in Z in order to improve the interpretation of the Y-part of the X/Y association. Two data sets are used to illustrate three-block bi-focal PLS (3BIF-PLS). Example I relates to single point mutants of haloalkane dehalogenase from Sphingomonas paucimobilis UT26 and their ability to transform halogenated hydrocarbons, some of which are found as organic pollutants in soil. Example II deals with soil remediation capability of bacteria. Whole bacterial communities are monitored over time using "DNA-fingerprinting" technology to see how pollution affects population composition. Since the data sets are large, hierarchical multivariate modeling is invoked to compress data prior to 3BIF-PLS analysis. It is concluded that the 3BIF-PLS approach works well. The paper contains a discussion of pros and cons of the method, and hints at further developmental opportunities. full article (in PDF format) |
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