The Integration And Application Of The Second Generation Sequencing Data Analysis Tools For Metabolic Network Analysis

The discovery of the double helix structure of the DNA molecule marks the leap from traditional biology to molecular biology. From the birth of the Sanger sequencing technology in the seventies of the 20 th century,thousands of eukaryotes and prokaryotes have been sequenced. researchers gradually began to study gene sequences- protein- biochemical reaction of biological information flows in biological systems, and dug out the molecular structure characteristics, biological network state information in the gene sequence.Based on the works of predecessors, this paper finds some information including the enzyme in the sequence by the transcriptome sequence,basicaclly form of the two generation of sequencing data to the metabolic network enzyme information annotation tools,, and basically completed the process from gene sequence to metabolic network analysis, which includes the integration of the two generation transcriptome sequencing data analysis tools, Enzyme sequence information database,and the comparison of metabolic network; The thesis integrates second generation transcriptome sequencing data analysis tools in Java desktop application, which is convenient for biologists to deal with biological sequence data; and constructs the localization of the enzyme sequence database based on the United States Center for Biotechnology Information DNA sequence database, Kyoto gene and genome database.It also quickly builds the metabolic network model by the sequence information of the enzyme and finishes the design of the metabolic network alignment algorithm. Finally, it was contrastively studies that intercomparison results, of the metabolic network of the enzyme and enzyme encoding sequence value based on the obtained, which indicates that the results of the enzyme sequence information can more reflect the evolutionary relationships between species.Experiments show that this study expands the application of next generation sequencing data, facilitates the enzymes study in the metabolic network for biologists, and provides multi angle of the metabolic network alignment analysis. It has important significance for the fermentation industry and biomedical research.