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Molecular factor analysis

C.D. Eads, C.M. Furnish, I. Noda, K.D.Juhlin, D.A. Cooper, S.W. Morrall, Molecular factor analysis applied to collections of NMR spectra. Anal. Chem. 76 (2004) 1982-1990. [Pg.146]

A factor analysis of the Raman spectra of a set of linear polyethylenes identified the existence of a third component in addition to the pure crystalline and pure amorphous components [78]. The characteristics of the Raman spectrum of the interphase were very similar to that of the crystalline spectrum indicating that the interphase retains a significant degree of order. Using the Raman method, the content of interphase in linear polyethylenes was found to increase with molecular weight [74—76,78]. For molecular weights below... [Pg.271]

The enthusiastic search for more and more transcription factors that ensued in the following decade diverted the attention of many molecular biologists from the fundamental problem of how transcription can be initiated or proceed in a chromatin matrix. However, three lines of research continued throughout the 1980s and 1990s that have converged with transcription factor analysis to build the detailed, if still confusing picture we have today. [Pg.8]

Boehm, M., Stuerzebecher, J., and Klebe, G. Three-dimensional quantitative structure-activity relationship analyses using comparative molecular field analysis and comparative molecular similarity indices analysis to elucidate selectivity differences of inhibitors binding to trypsin, thrombin, and factor Xa. /. Med. Chem. 1999, 42, 458-477. [Pg.373]

How is dimension reduction of chemical spaces achieved There are a number of different concepts and mathematical procedures to reduce the dimensionality of descriptor spaces with respect to a molecular dataset under investigation. These techniques include, for example, linear mapping, multidimensional scaling, factor analysis, or principal component analysis (PCA), as reviewed in ref. 8. Essentially, these techniques either try to identify those descriptors among the initially chosen ones that are most important to capture the chemical information encoded in a molecular dataset or, alternatively, attempt to construct new variables from original descriptor contributions. A representative example will be discussed below in more detail. [Pg.282]

Recently, Tichy investigated 41) the dependencies of the steric constants, Es, v, L, Bj, B4, MV (molar volume), [P] (parachor), MR (molar refraction), MW (molecular weight), and % (molecular connectivity index) on lipophilicity, as it is measured by n 42) and f43) constants. The data were treated by factor analysis methods. [Pg.104]

Vaz, R. J., McLEan, L. R., Pelton, J.T. Evaluation of Proposed Modes of Binding of (2S)-2-[4-[[(3S)-l-acetimidoyl-3-pyr-rolidinyl]oxyl]phenyl]-3-(7-amidino-2-naphthyljpropan oic Acid Hydrochloride and Some Analogs to Factor Xa Using a Comparative Molecular Field Analysis. [Pg.245]

Analyses of Pitch. Modern analytical facilities of high-pressure liquid chromatography, gel permeation chromatography, an(j 1 nuclear magnetic resonance and mass spectrometry, associated with 1R and UV spectroscopy enable a total molecular constituent analysis of pitch composition to be obtained. The use of such information could then possibly be the route to prediction of pitch quality on carbonization. It would appear that such an approach would not be successful (ignoring the cost factor for such detailed analysis). The pitch cannot be considered as an assembly of molecules which pyrolyse independently of each other. The pitch carbonizes as a multi-phase system and experience today would indicate the impossibility of predicting all interactions, physical and chemical. [Pg.23]


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