基于PCWM扫描模型的植物启动子分析及识别  

Analysis and Recognition of Plant Promoters Based on a Position-correlation Weight Matrix

作　　者：左永春[1] 李前忠[1] 杨磊[1] 杨乌日吐[1] 

机构地区：[1]内蒙古大学物理科学与技术学院,呼和浩特010021

出　　处：《内蒙古大学学报（自然科学版）》2008年第5期536-542,共7页Journal of Inner Mongolia University：Natural Science Edition

基　　金：国家自然科学基金项目(No.30560039)

摘　　要：启动子是基因转录调控机制中最重要的调控区域,启动子区域内转录元件的识别是揭示基因表达调控的重要基础.快速,可靠的启动子预测算法对于广范围内启动子元件的识别能够提供很大的帮助,目前的启动子识别算法及预测软件普遍存在假阳率高的缺点,因此改进识别算法的泛化能力显得尤为重要.本文利用从PlanPromDB数据库上下载的启动子数据,在深入分析启动子GC-Skew偏好、特异性位点保守性及TSS-TIS距离分布的基础上,通过改进原有位置权重矩阵(PWM)模型,构建出能够同时考虑位点保守性和关联性的位置关联性权重矩阵(PCWM)扫描模型,在此基础上利用标准化打分函数对植物TATA启动子进行预测,获得了较好的结果.Promoters are the most important regular elements in a transcription process. The recognition of transcription elements in the promoter regions is the base of revealing gene expression. Fast and reliable prediction algorithm can help to identify the promoter elements in the wide region to a large extent. However,the recognition results achieved by the current algorithms always take a lot of false positive. So it is essential to improve the recognition algorithm. By analyzing the conservation of the specific sites and TSS-TIS distance distribution of plant TATA promoter sequences downloaded from PlantPromDB,a new recognition program based on position correlation weight matrix （PCWM） is proposed. The better prediction results for plant TATA promoters are obtained by using standardization score functions.

关 键 词：TATA启动子 位置关联性权重矩阵(PCWM) 保守性 

分 类 号：Q61[生物学—生物物理学]