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近来,人们发现从疾病相关基因中寻找关键基因对疾病的诊断和治疗很重要。癌相关基因的网络是根据正常和患病的胶质瘤组织的基因表达谱建立。根据建立的基因网络和CIPHER方法,不同阈值下的正常和患病的胶质瘤表型网络被建立。根据已知的疾病和表型间的关联,另一组正常和患病的胶质瘤表型网络被建立。将两种方法建立的相应的表型网络进行比较,匹配度最大时对应的阈值及基因和表型网络被确定。在此基础上,通过打分方法得到了7个关键基因:DMBT1,ERBB2,NF2,PDGFB,AR,ARAF和TP53。文献查询发现其中5个基因与胶质瘤的形成和发展密切相关。剩下两个基因中的ARAF也间接地参与胶质瘤形成。因此,这两个基因可能在胶质瘤的形成中起重要作用。这一预测仍需要实验验证。
Recently, it has been found that it is very important to find out the key genes from disease-related genes for the diagnosis and treatment of diseases. The network of cancer-related genes is based on gene expression profiles of normal and diseased glioma tissues. Based on the established gene network and the CIPHER method, normal and diseased glioma phenotype networks were established at different thresholds. Based on the known association between disease and phenotype, another set of normal and diseased glioma phenotype networks was established. The corresponding phenotypic networks established by the two methods were compared and the corresponding threshold and gene and phenotypic networks were identified when the degree of matching was maximized. On this basis, seven key genes were obtained by scoring method: DMBT1, ERBB2, NF2, PDGFB, AR, ARAF and TP53. The literature search found that five genes are closely related to the formation and development of glioma. ARAF of the remaining two genes is indirectly involved in glioma formation. Therefore, these two genes may play an important role in glioma formation. This prediction still needs experimental verification.