Biomedical subjects

Zhuo Fang

Publications and source records attributed to Zhuo Fang.

3 recordsLinked to original sources

PubMed2006

Comparisons of graph-structure clustering methods for gene expression data.

Although many numerical clustering algorithms have been applied to gene expression data analysis, the essential step is still biological interpretation by manual inspection. The correlation between genetic co-regulation and affiliation to a common biological process is what biologists expect. Here, we introduce some clustering algorithms that are based on graph structure constituted by biological knowledge. After applying a widely used dataset, we compared the result clusters of two of these algorithms in terms of the homogeneity of clusters and coherence of annotation and matching ratio. The results show that the clusters of knowledge-guided analysis are the kernel parts of the clusters of Gene Ontology (GO)-Cluster software, which contains the genes that are most expression correlative and most consistent with biological functions. Moreover, knowledge-guided analysis seems much more applicable than GO-Cluster in a larger dataset.

Algorithms↗

PubMed2005

Knowledge guided analysis of microarray data.

To microarray expression data analysis, it is well accepted that biological knowledge-guided clustering techniques show more advantages than pure mathematical techniques. In this paper, Gene Ontology is introduced to guide the clustering process, and thus a new algorithm capturing both expression pattern similarities and biological function similarities is developed. Our algorithm was validated on two well-known public data sets and the results were compared with some previous works. It is shown that our method has advantages in both the quality of clusters and the precision of biological annotations. Furthermore, the clustering results can be adjusted according to different stringency requirements. It is expected that our algorithm can be extended to other biological knowledge, for example, metabolic networks.

Algorithms↗

PubMed2002

Adsorption of chloroacetanilide herbicides on soil and its components. III. Influence of clay acidity, humic acid coating and herbicide structure on acetanilide herbicide adsorption on homoionic clays.

Adsorption of chloroacetanilide herbicides on homoionic montmorillonite, soil humic acid, and their mixtures was studied by coupling batch equilibration and FT-IR analysis. Adsorption isotherms of acetochlor, alachlor, metolachlor and propachlor on Ca(2+)-, Mg(2+)-, Al(3+)- and Fe(3+)-saturated clays were well described by the Freundlich equation. Regardless of the type of exchange cations, Kf decreased in the order of metolachlor > acetolachlor > alachlor > propachlor on the same clay. FT-IR spectra showed that the carbonyl group of the herbicide molecule was involved in binding, probably via H-bond with water molecules in the clay interlayer. The type and position of substitutions around the carbonyl group may have affected the electronegativity of oxygen, thus influencing the relative adsorption of these herbicides. For the same herbicide, adsorption on clay increased in the order of Mg2+ < Ca2+ < Al3+ < or = Fe3+ which coincided with the increasing acidity of homoionic clays. Acidity of cations may have affected the protonation of water, and thus the strength of H-bond between the clay water and herbicide. Complexation of clay and humic acid resulted in less adsorption than that expected from independent adsorption by the individual constituents. The effect varied with herbicides, but the greatest decrease in adsorption occurred at a 60:40 clay-to-humic acid ratio for all the herbicides. Causes for the decreased adsorption need to be characterized to better understand adsorption mechanisms and predict adsorption from soil compositions.

Adsorption↗