ஜர்னல் ஆஃப் கம்ப்யூட்டர் சயின்ஸ் & சிஸ்டம்ஸ் பயாலஜி

Damage analysis in metabolic pathways is one of the most highlighted fields in systems biology area. Metabolic errors are studied with respect to inherited enzyme deficiencies. The damages usually occur due to changes in a particular enzymatic reaction or deletion of a step. Some enzyme disorders can also cause the particular reaction not to occur causing accumulation or reduced presence of a metabolite. This leads to dysfunction and disease state. Furthermore, the deletion of a path may change the end product of a reaction and can give rise to disorders. Thus, if the pathway leading to these changes can be determined, it would be easier to determine the disorders. Various statistical methods have been employed to determine the damages in the metabolic pathway. One such method is graph analysis technique. Here a graph is represented in the form of nodes and edges and the various properties may be determined. The wet lab results may be interpreted using statistics. Other studies of metabolomics can be performed using flux based analysis, fourier -transformation, Lp and power laws.

A total of fourteen specimens of three Fructus Evodiae species were collected from Zunyi and Tongren of Guizhou Province in China. The internal transcribed spacer (ITS) region (ITS1, ITS2 and 5.8S rDNA) of the nuclear ribosomal DNA (nrDNA) of the fourteen species were amplified and sequenced and another two sequences of Evodia rutaecarpa (JUSS.) BENTH species were obtained from Hunan Academy of Traditional Chinese Medicine, Changsha, Hunan Province of China. In addition to, the main ingredients of their medicinal chemistry of all specimens were identified by high performance liquid chromatography (HPLC). The three different morphological Fructus Evodiae species could not be distinctly classified by phylogenetic analysis of ITS combining the main ingredients of medicinal chemistry. This conclusion is inconsistent with early research results.

Tandem repeats (TR) are the most abundant ones in the extragenic region of genomes. Biologists have already found a large number of regulatory elements in this region. These elements may profoundly impact the chromatin structure formation in nucleus and also contain important clues in genetic evolution and phylogenic study. This study attempts to mine rules on how combinations of individual binding sites are distributed tandem repeats in human genome (http://www.trbase2.cn). The association rules mined would facilitate efforts to identify gene classes regulated by similar mechanisms and accurately predict regulatory elements. Herein, the combinations of transcription factor binding sites in the tandem repeats are obtained and, then, data mining techniques are applied to mine the association rules from the combinations of binding sites. In addition, the discovered associations are further pruned to remove those insignificant associations and obtain a set of discovered associations.