ANALYSIS OF ESCHERICHIA-COLI PROMOTER STRUCTURES USING NEURAL NETWORKS
ANALYSIS OF ESCHERICHIA-COLI PROMOTER STRUCTURES USING NEURAL NETWORKS
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DOI：
10.1093/nar/22.11.2158
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发表时间：
1994-06-11
影响因子：
14.9
通讯作者：
GHOSH, I
中科院分区：
文献类型：
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作者：
MAHADEVAN, I;GHOSH, I
训练BP神经网络对E.所有间隔类别（15至21）的大肠杆菌启动子。采用三模块方法，其中第一神经网络模块预测共有框，第二模块将启动子对齐到65个碱基的长度，第三神经网络模块预测65个碱基的整个序列，同时考虑启动子中碱基之间可能的相互依赖性。用106个启动子和富含60%AT的随机序列训练网络，并在126个启动子（细菌、突变体和噬菌体启动子）上进行测试。在5000个随机产生的序列上测试时，该网络在启动子识别方面的成功率为98%，在非启动子识别方面的成功率为90.2%。用p22ant启动子的11个突变的非启动子和8个突变的启动子进一步训练网络。鉴定了具有p22ant的7个突变启动子和13个突变非启动子的测试集。使用总共1665个启动子和非启动子数据对网络进行升级，以识别基因序列中的任何启动子序列。该网络鉴定了pBR322质粒中P1、P2和P3启动子的位置。还增加了通过字符串搜索程序搜索起始密码子、核糖体结合位点和终止密码子，以寻找可以产生蛋白质产物的可能启动子。该网络也成功地在合成质粒pWM 528上进行了测试。
Backpropagation neural network is trained to identify E. coli promoters of all spacing classes (15 to 21). A three module approach is employed wherein the first neural net module predicts the consensus boxes, the second module aligns the promoters to a length of 65 bases and the third neural net module predicts the entire sequence of 65 bases taking care of the possible interdependencies between the bases in the promoters. The networks were trained with 106 promoters and random sequences which were 60% AT rich and tested on 126 promoters (Bacterial, Mutant and Phage promoters). The network was 98% successful in promoter recognition and 90.2% successful in non-promoter recognition when tested on 5000 randomly generated sequences. The network was further trained with 11 mutated non-promoters and 8 mutated promoters of the p22ant promoter. The testing set with 7 mutated promoters and 13 mutated non-promoters of p22ant were identified. The network was upgraded using total 1665 data of promoters and non-promoters to identify any promoter sequences in the gene sequences. The network identified the locations of pi, P2 and P3 promoters in the pBR322 plasmid. A search for the start codon, Ribosomal Binding Site and the stop codon by a string search procedure has also been added to find the possible promoters that can yield protein products. The network was also successfully tested on a synthetic plasmid pWM528.