Research The Reconstruction Of Automation Metabolic Model On Pichia Stipitis

China is an agricultural country. Harvest crops will produce a large number of agricultural waste.One hand, because of the limited power, these agricultural waste are solved by wasting and burning, which not only failed to achieve the efficient use of the objective, but alse take the pressure to environment. On the other hand, along with the shortage of oil resources and focus on environmental issues, the researchers began to find a substitute for oil fuel alcohol (ethanol). Ethanol is a renewable resource, and efficient environmental protection, which can be made of crops for the production.Pichia stipitis got the attention of researchers,which has a great advantage as fermentation of natural cellulose to ethanol.The purpose of this study is how to product mass ethanol By rebuilding it’s genome scale metabolic network model (Genome Scale Metabolic Model, GSMM).analyzeing of metabolic networks can help people understand and use the cellular metabolic processes and promote the development of fermentation engineering, pharmaceutical and other industries.Genome scale metabolic network model (GSMM) is a metabolic network contacting gene,protein and biochemical reactions(G-P-R).We can get the best way for the specific target, and provides a basis for the experimental to obtain product through the analysis on the model.So far, the speed of genome sequencing is much faster than the speed of construct GSMM.There are two reasons.First, the few knowledge of the physiological and biochemical mechanism of many species. Second,construct one model requires a lot of manpower to deal with large amounts of data, a model of the time required for 6 months-2 years.In this case,this paper proposes a automation reconstruction of research genome metabolic network.In this project, there is part of the work:Firstly, automation construct of genome scale metabolic network by computer language.We need construct three initial models, which based on different the original data.The three model are:the model based on online database of KEGG,the model based on the local database of Uniprot-MetaCyc,the model based on homologous alignment. This step has a difficulty that the models above have different data sources and different biochemical reaction.So,In this paper put forward the Euclidean distance matching method based on the reaction type.We also need to modify the model by document data and the COBRA tools. Establish a rapidly positioning keyword position in the local literature function,In order to search for documents quickly.At last,we get a final P.stipitis CBS 6054 model.This model is developed on the platform of Eclipse by Java language.Secondly, in order to metabolic pathway contains the most simple gene was a prediction of normal cell growth state, the refined model of the obtained genome simplify operation.By calculating the maximum growth rate of the fine model initial value, does not affect the model of the initial value condition, simplified genome. In the reaction of non essential gene knockout, the principle of using a genetic algorithm.Metabolic pathway finally get a set of prediction of normal cell growth contains the most simple genetic condition, provides the reference for the purpose of biological wet experimental design of genome. This part is programming on the Matlab platform, useing the COBRA tool.