초록 ▼

­ 초기 가상세포 모델과 대사 네트워크 DB 분석결과 제시­ 대사네트워크 구성 기법 개발 및 신규 게놈 서열 완성 균주 대상으로 구성 전략 개발­ 이종 DB 통합을 위한 DBMS 시스템 및 검색, 정보 연관성 추출 시스템 개발­ Lactococcus lactif 균주의 네트워크 모델 구축 및 동역학 시뮬레이션 수행­ 대장균 및 재조한 대장균의 발효를 통해 1000종 이상의 대사데이터를 확보­ 다양한 조건 하에서 대사흐름평형 기술 개발 및 데이터 확보­ 다양한 조건에서 transciptome, proteome, fluxome 데이터

­ 초기 가상세포 모델과 대사 네트워크 DB 분석결과 제시­ 대사네트워크 구성 기법 개발 및 신규 게놈 서열 완성 균주 대상으로 구성 전략 개발­ 이종 DB 통합을 위한 DBMS 시스템 및 검색, 정보 연관성 추출 시스템 개발­ Lactococcus lactif 균주의 네트워크 모델 구축 및 동역학 시뮬레이션 수행­ 대장균 및 재조한 대장균의 발효를 통해 1000종 이상의 대사데이터를 확보­ 다양한 조건 하에서 대사흐름평형 기술 개발 및 데이터 확보­ 다양한 조건에서 transciptome, proteome, fluxome 데이터 확보­ 유전자 조절 네트워크 구축을 위한 네트워크 시스템 개발

Abstract ▼

The objective of this project is the construction of metabolic network and the development of virtual cell system which is capable of quantitative and qualitative analysis of metabolic pathways. This includes the development of genome-scale metabolic network of microorganisms and quantitative! quali

The objective of this project is the construction of metabolic network and the development of virtual cell system which is capable of quantitative and qualitative analysis of metabolic pathways. This includes the development of genome-scale metabolic network of microorganisms and quantitative! qualitative analyses of the model.We developed the methods for the construction of genome-scale metabolic network. Based on the constructed metabolic networks, skills for the flux balance analysis were developed. More than 1,000 set of metabolic data were generated from the experiments to support the constructed model. Additionally, more than 10 set of transcriptome and proteome data for the E. coli and recombinant E. coli were obtained by the DNA chip and 2-D gel experiments. The raw data were further analyzed to find physiological characteristics and applications. We collected the information of the core models in systems biology and developed the model libraries by accumulating various compatible network models such as SBML, CellML. Gene regulatory network tools (GeneRUBY and MONET) were developed using the Bayesian network model and biological data clustering model. The schema of the various public databases were anlayzed to develop an integrated querying system. UML descriptions of each database were generated as a result of the analyses. Based on the descriptions, integrated querying systems for the biological informations (BIRDIE and UNlCORN) were developed using the mediator-wrapper structure. We constructed the strict metabolic network model of Lactacaccus lactis mainly focused on the lactate metabolism. The constructed metabolic network was analyzed by applying the in vitro experiment using the sampling equipment and in silica network analysis using GEP ASI simulation tool. Parameter estimation of the dynamic model of Lactacoccus lactis was performed using the GEP ASI simulation tool by utlizing the experimenta data.The improved metabolic network models of E. coli and fermentation data can be used for the I metabolic flux analysis and flux estimation to the improved strains. Collected transcriptome, proteome and fluxome data can be used as a foundation system for the integration of multi-dimensional network model. The developed systems can be used for the prediction of genetic interactions and improvement of the research efficiency.