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Research On SiRNA Sequence Design In RNAi Technology

Posted on:2007-10-11Degree:MasterType:Thesis
Country:ChinaCandidate:J L LiFull Text:PDF
GTID:2120360215470227Subject:Control Science and Engineering
Abstract/Summary:PDF Full Text Request
RNAi is a phenomenon of gene silence induced by double-stranded RNA(dsRNA) that is homologous to target gene. Target mRNA is degraded by short interfering RNA that is homologous to it so that the process of synthesizing protein is interfered. RNAi is a kind of new technology that can be used in identifying the function of gene, curing desease and research on antivirus of plant, and so on.In the application of RNAi, the sequence design of siRNA is very important. Mammalian genen typically includes several thousand nucleotides, however the designed siRNA includes only about 19 nucleotides, so the num of target sites of gene that can be choosen is large. It shows that different target site choosing affect siRNA activity. siRNA may inhibite target impression very well if the target site is choosen properly, but it is possible that siRNA hardly work when choosing wrong target site. Thinking of the cost and condition of experiment, it is unpratical to test very site of target gene one by one, so researching the factors of affecting siRNA activity is essential.In this article, the research on factors affecting the siRNA activity is from two aspects:(1) the motifs of siRNA, (2) the motifs and second structures of target mRNA. After figuring out the factors of affecting siRNA activity, back-propagation neural network is built and trained using some publised data of experiments, then the network is used to predict siRNA activity. At last, the information of target mRNA sencond structure is used to filter the outputs of BP ANN network. The computer simulation results show that in predicted active siRNAs there are more than 80% siRNAs are really active, so this method can provide reference service for designing siRNA.
Keywords/Search Tags:RNAi, siRNA, target mRNA, sequence design, target site, back-propagation neural networ
PDF Full Text Request
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