-
[show abstract]
[hide abstract]
ABSTRACT: Liquid state methanol and ethanol under different temperatures have been investigated by FT-NIR (Fourier transform nearinfrared)
spectroscopy, generalized two-dimensional (2D) correlation spectroscopy, and PCA (principal component analysis). First, the
FT-NIR spectra were measured over a temperature range of 30–64 (or 30–71) °C, and then the 2D correlation spectra were computed.
Combining near-infrared spectroscopy, generalized 2D correlation spectroscopy, and references, we analyzed the molecular structures
(especially the hydrogen bond) of methanol and ethanol, and performed the NIR band assignments. The PCA method was employed
to verify the results of the 2D analysis. This study will be helpful to the understanding of these reagents.
KeywordsNIR (near-infrared)-two-dimensional (2D) correlation spectroscopy-principal component analysis (PCA)-methanol-ethanol
Science China-Chemistry 05/2012; 53(5):1155-1160. · 1.02 Impact Factor
-
Expert Syst. Appl. 01/2010; 37:5032-5039.
-
[show abstract]
[hide abstract]
ABSTRACT: The structure-activity relationship study of C-10 substituted artemisinin (QHS) derivatives that are used as antimalarial
was performed with the RS (rough sets) method. An RS process is a concise nonlinear process, and it has broad application
foreground in the data mining of nonlinear life courses. In this work, initially the parameters of C-10 substituted QHS’s
derivatives were computed with the quantum chemistry method, and the information table was constructed from the parameters
(condition attributes) and biological activity (decision attributes). Based on the analysis of rough set theory, the core
and reduction of attributes sets were obtained. Then the decision rules were extracted and the structure-activity relationship
was analyzed. As a nonlinear system, RS theory can extract the special relation in the database. It has the advantage of being
nonlinear over multiple linear regression (MLR), principal component analysis (PCA), partial least square (PLS), etc., and
the advantage of obtaining results with unambiguous physical meanings over artificial neuron networks (ANNs), etc. The result
obtained in this study is instructive to the study of pharmacodynamics, resistance mechanism of QHS and development of QHS’s
derivatives.
Science in China Series B Chemistry 09/2008; 51(10):937-945. · 1.20 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: Four aromatic medicines (acetaminophen; niacinamide; p-aminophenol; nicotinic acid) containing nitrogen were investigated by FT-NIR (Fourier transform near-infrared) spectroscopy and generalized two-dimensional (2D) correlation spectroscopy. The FT-NIR spectra were measured over a temperature range of 30-130 degrees C. By combining near-infrared spectroscopy, generalized 2D correlation spectroscopy and references, the molecular structures (especially the hydrogen bond related with nitrogen) were analyzed and the NIR band assignments were performed. The results will be helpful to the understanding of aromatic medicines containing nitrogen and the utility of these substances.
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy 04/2008; 71(4):1228-33. · 2.10 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: Fructus Lycii is a traditional Chinese medicinal herb. The objective of this paper was to apply two-dimensional (2D) near-infrared (NIR) correlation spectroscopy to the discrimination of Fructus Lycii of four different geographic regions. Generalized 2D-NIR correlation spectroscopy was able to enhance spectral resolution, simplify the spectrum with overlapped bands, and provide information about temperature-induced spectral intensity variations that was hard to obtain from one-dimensional NIR spectroscopy. The 2D synchronous and asynchronous spectra showed remarkable differences within the range of 4950-5700cm(-1) between samples of different geographic regions. Using NIR instead of IR made the 2D approach more convenient and fast, and it can be applied to more area like process control. This approach can also be applied analogously to the discrimination of other Chinese herbal medicine of different geographic regions.
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy 03/2008; 69(2):580-6. · 2.10 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: Rough set algorithm was used as a new methodology to build structure–activity relationship (SAR) models in this paper. It acted as feature selector and nonlinear rule generator. The SAR model expressed as human readable if-then rules was developed for the inhibition of the serine/threonine kinase CDK1/cyclinB by compounds from the indirubin inhibitor family. The feature selection ability of rough set algorithm was compared with the build-in approaches (CfsSubsetEval and ConsistencySubsetEval) in Weka under leave-one-out (LOO) and 10-fold cross-validation. Through training a set of 31 objects, a rule-based SAR model had been built with a reduct generated by rough set. The predictability of the model was evaluated by an external test set of 16 compounds. The existing powerful approaches, such as the decision tree learners, neural network, support vector classifier and LogitBoost approaches, were used to verify the performance of rough set method. It revealed that rough set method should play important role in data preprocessing and model building of nonlinear SAR analysis. The advantages and limitations of rough set-based SAR analysis were discussed. The results were satisfactorily in accordance with the available understanding of cocrystal structures and 3D QSAR models.
Expert Systems with Applications.
