利用Weka挖掘白血病与基因的关系

目的:使用Weka挖掘白血病与基因关系。方法:检索PubM ed数据库,获得研究数据;利用BICOMB抽取主要主题词和副主题词,生成高频词共现矩阵和词篇矩阵,利用Weka平台、采用Cobweb算法对共现矩阵数据进行聚类分析得到研究热点和进行文献验证。结果:Weka将42个高频词聚为7类,代表白血病与基因的7个可能联系,但第1,2,4,5类中没有白血病或基因高频词,聚类效果较差,其余类聚类效果较好。结论:聚类分析发现白血病与myc基因、abl基因、p53基因、病毒基因、免疫球蛋白基因和mdm基因有关。

Mining the relation between leukemia and genes using Weka

Objective To mine the relation between leukemia and genes using Weka.Methods The papers on leukemia and genes were retrieved from PubMed, their subject headings and subheadings were extracted using BICOMB to generate co-occurrence matrix and term-paper matrix. The research hotspots were found by cluster analysis of the data on co-occurrence matrix using Weka and Cobweb.The literature was verified.Results The 42 high frequency words were clustered into 7 classes by Weka. No high frequency words of leukemia or genes were found in classes 1, 2, 4 and 5, indicating that their clustering efficiency was poor. The clustering efficiency of the other 3 classes was good. Conclusion Cluster analysis showed that leukemia is related with myc gene, ab1 gene, p53 gene, virus gene, immunoglobulin gene and mdm gene.