Design And Implementation Of Data Warehouse Base On The Disease And Pathogenic Marker Detecting System

In the appearance of some kind of diseases, especially cancer, the expressions of gene or protein in the body will always be abnormal. We can diagnose some kind of diseases by detecting the expression of gene or protein. In the field of cancer surgery, so far. the effective method is to detect the values that these abnormal gene or protein express. We estimate the expression according to the statistic analysis of historical data. We consider that some kind of cancer or disease is detected when the relational gene or protein expression is abnormal. Base on this theory, we build a data model which consists of six tables in the oracle database. By querying the relational tables we can get the relation between a disease and its pathogenic marker (gene or protein), thereby, we can make a conclusion that those markers we find are the pathogenic markers to a certain disease. The oracle database stores huge amounts of information. The oracle database is designed for capturing data, while the data warehouse is for data analysis. For the further analysis we will build a multidimensional data model, the model is consists of dimension tables and fact tables. The dimension tables describe the detailed information of disease and gene tables, and the fact tables store the measures we judge a disease and its pathogenic markers. We can get the necessary information by querying the fact tables. We also introduce the particle-size which plays an important role in the data warehouse designing thereby we can do our research in different levels.Firstly this article introduces our d-marker database including the data model and the table attributes. Secondly the basic architecture of data warehouse and the difference between traditional database and data warehouse are introduced in addition we also introduce the OWB and OLAP technology. In chapter three we design the data warehouse, including the configuration of project setting and designing procedure. At last we build an OLAP multidimensional data set. This article is to explore the application of data warehouse in the field of bio-information. At present the data scale of bio-information is huge and the noise of the data is also enormous, so the data warehouse will play an important role in this field.