Reasearch On Gene Chip Data Processing Bioinformatics Method Of Carcinoma Of Stomach Based On The Cluster Analysis Algorithms

Gastric cancer is clinically common malignant tumor, its pathogenesis and other tumors, is similar to the environmental factors and genetic factors. In the two factors, the long-term effects of patient airframe gene mutation, eventually lead to cancer. Because of the stomach is a slow process, so the genes for the early diagnosis is extremely important. Gene chip technology is a new technology in recent years, its characteristic is to provide an experiment in the laboratory information, reduce the massive cost. However, due to the analysis of the information for gene chip to the background knowledge of computer science, many medical researchers cannot directly on the experiment data obtained in data mining. Therefore, to develop a medical researchers use of gene microarray analysis platform is necessary. The main work is established based on the cluster analysis algorithm of gene microarray data analysis platform for biology gene microarray data analysis, and provide a powerful tool for early diagnosis of cancer provides a new method.Objective: To develop a gene chip information processing bioinformatics platform, the platform for clinical data of patients with analysis of information and deal with the function of gene chip information. Methods: The collection of clinical surgery in patients with gastric cancer tissue and normal gastric tissue specimens, extraction of total tissue RNA, the application of Affymetrix Human Exon 1.0 ST Array Detection of mRNA expression of tissue, the Expression Console software applications available to Affymetrix Human Exon 1.0 ST Array of picture information, such as Signal Histogram be the result of a preliminary analysis, and text into a TXT. Application of JSP technology, the establishment of Web site forms of gene chip data processing platform, and its function for the importation of Affymetrix Human Exon 1.0 ST Array chips TXT format, the platform will automatically use the clustering algorithm analysis chip information, to receive the gene may function similar to the serial number ; another feature of the site entered into the system for the analysis of DNA microarray in patients with clinical information obtained may be related to gastric cancer subtypes and clinical stages of gastric cancer-related clinical factors. In this paper, bio-informatics platform analysis of 70 cases of clinical subtypes of patients with gastric cancer, gastric cancer and clinical stage may be the correlation between factors; through the analysis of simulation data confirm the analysis of DNA microarray platform at the time of the reliability of the information. Results: The establishment of processing DNA microarray bioinformatics information platform; In this paper, bio-informatics platform, studied with different types of 70 cases of gastric cancer patients, 47 cases were selected from studies of patients with gastric cancer subtypes and age, sex, weight, smoking and drinking habits of the relationship between factors; 68 cases were selected from studies of patients with gastric cancer staging and age, sex, weight, smoking and drinking habits of the relationship between factors. Platform with a functional analysis of gene function, the output of the results with relevant or similar function of the gene cluster. Conclusion: 1, the establishment of gene chip data processing platform, the platform has the clinical data of patients and statistical analysis of DNA microarray analysis of gene function on the relevance of the function; 2, the application of established bioinformatics platform to deal with the test The clinical data obtained better results.The cluster analysis algorithm based on the analysis of gene microarray data platform is the application of clustering, without supervision under the condition without prior knowledge of the way, the screening and to maximize the information related to the stomach, avoid the a priori knowledge may be some mistake. This platform has facilitate medical researchers use, The requirements for computer low, Expandability etc. Platform in dealing with artificial simulation data obtained the expected result, is a very promising bioinformatics tools.