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作 者:刘云卿[1,2] 黄荧[3] 周运[2,4] 李钧涛[3] 徐存拴
机构地区:[1]河南师范大学生命科学学院,河南新乡453007 [2]省部共建细胞分化调控国家重点实验室培育基地,河南新乡453007 [3]河南师范大学数学与信息科学学院,河南新乡453007 [4]河南师范大学计算机与信息工程学院,河南新乡453007
出 处:《河南科学》2013年第7期964-967,共4页Henan Science
基 金:国家973项目前期研究专项基金资助项目(2010CB534905)
摘 要:从生物高通量检测数据中挖掘关键基因/蛋白是生物信息学的重要研究内容.用大鼠基因组表达谱芯片Rat Genome 230 2.0检测大鼠肝再生中肝细胞的基因表达丰度和计算它们与对照的比值(ratio值),用F检验发现,Ccne1、Eg f、Met等8419个基因与大鼠肝再生相关.用过滤法从中筛选出3202个差异基因,用同类提取法从差异基因筛选出1000个特征基因.取前100个特征基因作为初选基因,进一步用序列向前法计算发现,Ccnd1、Grin2a、Spsb4等7个基因满足肝再生候选关键基因的条件.再用同类提取法分析发现,上述7个基因中,Ccnd1和Agtr1的关联度≥100,且文献报道与肝再生相关,当属关键基因.用机器学习法检验关键基因的正确性发现,同类提取法结合序列向前法预测的关键基因正确率达97%以上.因此,用该方法预测关键基因切实可行,值得推广应用.Selecting the key genes/proteins from the biological high-throughput detection data is important research content in bioinformatics. In this paper,Rat Genome 230 2.0 Array was used to detect expression abundance of rat hepatocyte genes in liver regeneration and to calculate their rate(ratio value). F-test found that 8419 genes (Ccne1,Eg f,Met,etc.) of rat hepatocyte were associated with liver regeneration. Then filter method was used to calculate the differential expression genes in the 8419 genes,of which 3202 genes were found to be the differential genes,and same kind extraction method to the feature genes in the 3202 genes,among them 1000 genes belong to the feature genes. After that,the first 100 feature genes were choose as the primary genes,and they were further calculated by the sequential-forward-selection method and found that 7 genes Ccnd1,Grin2a,Spsb4,etc.,may be the candidate key genes. Further same kind extraction method analyzing the 7 genes found that Ccnd1 and Agtr1 should be the key genes of rat liver regeneration,because their relevancy is greater than 100 and reported liver regeneration-related. The results were tested by machine learning method and found that accuracy of predi cted key genes is more than 97%. So the method of predicting key genes is feasible and worthy to application.
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