Cluster significance

Cronin MTD. The use of cluster significance analysis to identify asymmetric QSAR data sets in toxicology. An example with eye irritation data. SAR QSAR Environ Res 1996 5 167-75. 

In the tetranuclear clusters significant steric control of substitution with tertiary phosphines and phosphites is generally only observed in the fourth substitution step. The synthesis of tetra-substituted derivatives, therefore, requires more severe conditions22,46,86,248 and then breaking of the cluster can become important. 

As mentioned in my report, an ionic guest molecule in a host lipid bilayer (VIII) does not cluster significantly, whereas a similar but neutral guest (VII) clusters extensively as hexamers. I would expect this clustering to depend strongly on ionic strength only if the host lipids were charged. 

CA indicates three clusters of variables according to the less restrictive criterion of Sneath s index of cluster significance (2/3 of Dmax, where Dmax is the maximum distance) N02 and 02 Fe2+, SO -, NII4, N-DISS, COD, OXIS, and BOD and CP, NO3, DISS, Ca2+, and pH (Figure 15.3). 

There are exceptions from this trend. A noted example is the polarizability of sodium clusters significantly underestimated by semi-local functionals.73... 

This can be ascribed to the fact that Li atoms are virtually in the Li+ state and make slight covalent interaction with the surrounding atoms. The location of Li+ therefore does not affect the electronic states of the clusters significantly. 

This approach, originally proposed for binary response variables [McFarland and Cans, 1986], was extended to the quantitative biological responses y, scaled between zero and one [Rose and Wood, 1998] and then called Generalized Cluster Significance Analysis (GCSA). 

McFarland, J.W. and Gans, D.J. (1990a). Cluster Significance Analysis A New QSAR Tool for Asymmeric Data Sets. Drug InfJ., 24,705-711. 

McFarland, J.W. and Gans, DJ. (1990b). Linear Discriminant Analysis and Cluster Significance Analysis. In Quantitative Drug Design. Vol. 4 (Ramsden, C.A., ed.), Pergamon Press, Oxford (UK), pp. 667-689. 

Ordorica, M.A., Velazquez, M.L., Ordorica, J.G., Escobar, J.L. and Lehmann, P.A. (1993). A Principal Component and Cluster Significance Analysis of the Antiparasitic Potency of Praziquantel and Some Analogs. Quant.Struct.-Act.Relat., 12,246-250. 

Rose, V.S. and Wood, J. (1998). Generalized Cluster Significance Analysis and Stepwise Cluster Significance Analysis with Conditional Probabilities. Quant.Struct.-Act.Relat., 17,348-356. 

Cluster significance analysis (CSA) is a related, supervised method that can be used to determine subsets of properties that cause active compounds to cluster together. ... 

Rose, V. S., Wood, J. Generalized cluster significance analysis and stepwise cluster significance analysis with conditional probabilities. Quant. Struct.-Act. Relat. 1998,17, 348-356. 

McFarland, J.W. and Cans, D.J. (1995) Multivariate data analysis of chemical and biological data cluster significance analysis, in Chemometrics Methods in Molecular Design, Vol. 2 (ed. H. vandeWaterbeemd), VCH Publishers, New York, pp. 295-308. 

Besides the classical Discriminant Analysis (DA) and the k-Nearest Neighbor (k-NN), other classification methods widely used in QSAR/QSPR studies are SIMCA, Linear Vector Quantization (LVQ), Partial Least Squares-Discriminant Analysis (PLS-DA), Classification and Regression Trees (CART), and Cluster Significance Analysis (CSA), specifically proposed for asymmetric classification in QSAR. 

Table 7 provides the valu of iog /iog term for several types of defect clusters (MNDO force field model) [93]. It is shown that for the defects of types A and B (Fig. 7) these values are rather large, and endohedral clusters significantly influence the properties of the superconductive state. However, utilization of endohedral clusters as the pinning centers requires further research because in the fiame of this approach it is not possible to take into account electron-phonon interactions. 

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