Biomedical subjects

Yi-Zeng Liang

Publications and source records attributed to Yi-Zeng Liang.

5 recordsLinked to original sources

PubMed2003

Information theory applied to chromatographic fingerprint of herbal medicine for quality control.

At present, the construction of chromatographic fingerprints plays an important role in the quality control of complex herbal medicines. In this work, information theory was applied to obtain chromatographic fingerprints with good performance. Moreover, according to the characteristics of the chromatographic fingerprints obtained, some modifications of the calculation of the information content were conducted. In comparison with the information content from several chromatographic fingerprints obtained, reliable chromatographic fingerprints with a high separation degree and uniform concentration distribution of chemical components could be determined. The successful application of information theory with modification to simulated chromatographic fingerprints together with real herbal medicines such as Rhizoma chuanxiong and Ginkgo biloba from different sources demonstrated clearly that the proposed method to determine chromatographic fingerprints was reasonable and reliable and it was user-friendly. Chromatographic fingerprints determined with high separation degrees and uniform concentration distribution of chemical ingredients might also chemically represent characteristic components of herbal medicines for quality control.

Chromatography↗

PubMed2003

Two-step multivariate adaptive regression splines for modeling a quantitative relationship between gas chromatography retention indices and molecular descriptors.

The relationship between retention indices and molecular descriptors of alkanes is established by two-step multivariate adaptive regression splines (TMARS). TMARS combines linear regression with multivariate adaptive regression splines (MARS). It is demonstrated for the present data set that using linear regression or MARS modeling alone causes lack of fit. TMARS avoids lack of fit and appreciably improves the prediction ability for the model. The use of this combined approach permits the development of additional understanding of the adaptive nature in MARS modeling.

Chromatography, Gas↗

PubMed2003

Chemical rank estimation by noise perturbation in functional principal component analysist.

Some kinds of chemical data are not only univariate or multivariate observations of classical statistics, but also functions observed continuously. Such special characters of the data, if being handled efficiently, will certainly improve the predictive accuracy. In this paper, a novel method, named noise perturbation in functional principal component analysis (NPFPCA), was proposed to determine the chemical rank of two-way data. In NPFPCA, after noise addition to the measured data, the smooth eigenvectors can be obtained by functional principal component analysis (FPCA). The eigenvectors representing noise are sensitive to the perturbation, on the other hand, those representing chemical components are not. Therefore, by comparing the difference of eigenvectors obtained by FPCA with noise perturbation and by traditional principal component analysis (PCA), the chemical rank of the system can be achieved accurately. Several simulated and real chemical data sets were analyzed to demonstrate the efficiency of the proposed method.

Journal Article↗

PubMedDate not supplied

Analysis of volatile fractions of Schisandra chinensis (Turcz.) Baill. using GC-MS and chemometric resolution.

The two-dimensional data obtained from GC-MS has been used qualitatively and quantitatively to determine the components of the volatile fractions of Schisandra chinensis obtained by six different extraction methods. Sub-window factor analysis (SFA) was employed to confirm the identities of components determined in different samples. With the help of SFA, and other chemometric techniques, peak purity in the chromatograms was determined, and overlapping peaks were resolved to yield a pure chromatographic profile and mass spectrum for each component. It is demonstrated that the accuracy of qualitative and quantitative analysis may be greatly enhanced using chemometric resolution methods, such methods being particularly valuable with respect to the analysis of complex samples such as traditional Chinese medicines. It is further demonstrated that different extraction methods give rise to volatile fractions of S. chinensis which differ qualitatively and quantitatively in their composition.

Gas Chromatography-Mass Spectrometry↗

PubMedDate not supplied

External factor variable connectivity index.

A new variable index, external factor variable connectivity index (EFVCI), is proposed, in which the atomic attribute is divided into two parts. The innate part is denoted as outer-shell electrons and external part or perturbation by other atoms is represented as summation, multiplied by a variable x, of squared reciprocal matrix of i row (corresponds to atom A(i)). The division of atomic attribute in EFVCI is interpreted by using topological structure. In the correlation of boiling point of 149 acyclic alkanes, the optimal values will approach to a constant at -0.29 by using the zero to higher order indices of the same series. The new index, with high regression quality (R = 0.9986, s = 2.26, and F = 7088.4), is compared favorably with variable connectivity index and molecular connectivity index.

Journal Article↗