人Daintain 基因5'调控区序列的生物信息学分析

目的：探讨人Daintain 基因5''调控区的序列特征。方法：利用在线软件BLAST、Neural Network Promoter Prediction、Promoter 2.0、Promoter SCAN、EMBOSS、CpG Island Searcher 和TF SEARCH预测人Daintain 基因启动子区域、CpG 岛分布和转录因子结 合位点。结果：人Daintain 基因5''调控区存在1 个CAAT盒。Daintain 基因可能存在6 个启动子位点,CpG岛可能位于216 bp 区 间( 23 ~ 238 bp)。评分85 分以上时,该序列存在251 个可能的转录因子结合位点;评分90 分以上时,该序列存在70 个可能的转 录因子结合位点;评分95 分以上时,该序列存在16个可能的转录因子结合位点;评分100 分以上时,该序列存在7 个可能的转 录因子结合位点;这些结合的转录因子基本是与免疫细胞增殖或性别发生有关。结论：人Daintain 基因5''调控区的生物信息学研 究表明其转录受甲基化和多种转录因子的调控,为研究Daintain 基因启动子的功能提供理论基础。     

Neural network models for promoter recognition

The problem of recognition of promoter sites in the DNA sequence has been treated with models of learning neural networks. The maximum network capacity admissible for this problem has been estimated on the basis of the total of experimental data available on the determined promoter sequences. The model of a block neural network has been constructed to satisfy this estimate and rules have been elaborated for its learning and testing. The learning process involves a small (of the order of 10%) part of the total set of promoter sequences. During this procedure the neural network develops a system of distinctive features (key words) to be used as a reference in identifying promoters against the background of random sequences. The learning quality is then tested with the whole set. The efficiency of promoter recognition has been found to amount to 94 to 99%. The probability of an arbitrary sequence being identified as a promoter is 2 to 6%.