摘要
随着生物高通量分析技术的发展，获得基因组／蛋白组数据已较易实现．然而解析这些数据的生物学意义尚有不少困难，亟待克服．从生理反应的多样性、多步骤性、可逆性、循环性、重复性、网络性、可控性、适应性等特点入手，以基因表达丰度为基础，根据时间序列分析原理，应用皮尔森相关系数建立了两种描述基因协同作用的谱函数E。（￡）和巨，用它们分析基因表达丰度、表达变化预示的大鼠肝再生中肝细胞的增殖活动．结果显示，大鼠肝再生的进展阶段，即PH后12～72h肝细胞的增殖活动显著强于对照．进一步分析相关文献资料发现，上述结果与文献报道一致，表明在解析生物高通量分析数据的生物学意义方面，基因协同作用算法有一定应用价值．
Obtaining the data of genomics and proteomics has become reality following the development of the high-throughput biological analysis technology. However, it is necessary to do more works in analyzing their biological significance. For this, two algorithms describing gene synergy Ep（t） and E were established in the paper, following the features of biological processes, including diversity, multiple-steps, reversibility, circularity, cross- talk, repeatability,regularity,adaptation etc,based on quantitative gene expression profiling and time sequence analysis theory, and coupled to Pearson＇s correlation coefficient （r~）. The algorithms were used to analyze the biological significance of gene expression abundances of rat hepatocytes in liver regeneration, finding that proliferation of rat hepatocytes displayed significant differences from control in process stage, e.g.12~72 h, which were consistent with other reported experimental results, suggesting that the algorithms of gene synergy are reasonable, scientific and useful in analyzing the biological significance of the high-throughput test data.
出处
《河南科学》
2013年第10期1615-1619,共5页
Henan Science
基金
国家973项目前期研究专项基金资助项目(2012CB722304)
关键词
大鼠肝再生
基因芯片
基因表达丰度
基因协同作用
肝细胞增殖
rat liver regeneration
Rat Gemone Array 230 2.0
gene expression abundance： gene synergy
hepatocyte proliferation
