Predicting siRNA activity based on back-propagation
neural network

doi:10.1007/s11515-008-0032-z

Front. Biol.

2008, Vol. 3

Issue (2) : 154-159 https://doi.org/10.1007/s11515-008-0032-z

Predicting siRNA activity based on back-propagation neural network

LI Jianlong, WANG Zhengzhi, WANG Xiaomin

Institute of Mechanical Engineering and Automation, National University of Defense Technology

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Abstract RNA interference (RNAi) is a phenomenon of gene silence induced by a double-stranded RNA (dsRNA) homologous to a target gene. RNAi can be used to identify the function of genes or to knock down the targeted genes. In RNAi technology, 19 bp double-stranded short interfering RNAs (siRNA) with characteristic 3′ overhangs are usually used. The effects of siRNAs are quite varied due to the different choices in the sites of target mRNA. Moreover, there are many factors influencing siRNA activity and these factors are usually nonlinear. To find the motif features and the effect on siRNA activity, we carried out a feature extraction on some published experimental data and used these features to train a back-propagation neural network (BP NN). Then, we used the trained BP NN to predict siRNA activity.

Issue Date: 05 June 2008

Cite this article:

LI Jianlong,WANG Zhengzhi,WANG Xiaomin. Predicting siRNA activity based on back-propagation neural network[J]. Front. Biol., 2008, 3(2): 154-159.

URL:

https://academic.hep.com.cn/fib/EN/10.1007/s11515-008-0032-z
https://academic.hep.com.cn/fib/EN/Y2008/V3/I2/154

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