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siRNA interference efficiency prediction system based on arm microprocessor

A microprocessor-based, efficient technology, applied in the field of bioinformatics research, can solve problems that do not consider mRNAmotif features, structural features, etc.

Inactive Publication Date: 2016-04-20
JILIN UNIV
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AI Technical Summary

Problems solved by technology

At present, most of the siRNA efficiency predictions consider the characteristics of siRNA, the energy characteristics of double strands, etc., but do not consider the motif characteristics and structural characteristics of mRNA.

Method used

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  • siRNA interference efficiency prediction system based on arm microprocessor
  • siRNA interference efficiency prediction system based on arm microprocessor
  • siRNA interference efficiency prediction system based on arm microprocessor

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Embodiment Construction

[0041] The present invention is a new method for predicting siRNA interference efficiency based on ARM microprocessor, such as figure 1 As shown, the obtained siRNA sequence is input into CPLD, and the siRNA sequence is encoded through the feature extraction rule table, so that the siRNA sequence is stored in the SRAM in the form of a coding sequence, and then the ARM microprocessor is used to predict the efficiency of siRNA interference. It is necessary to establish a regression model based on random forest first, and adjust the parameters to minimize the generalization error of the model, and then load the digital information corresponding to the siRNA sequence to be predicted into the established random forest model to predict the interference efficiency , and finally output the predicted results to the LCD liquid crystal display.

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Abstract

The invention provides a method for forecasting siRNA (Small interfering Ribonucleic Acid) interference efficiency during RNA (Ribonucleic Acid) interference, relates to the field of bioinformatics research, and aims to solve the problem of poor accuracy rate in existing methods for forecasting siRNA interference efficiency. The method comprises the following steps: inputting an siRNA sequence into a CPLD (Complex Programmable Logic Device); extracting a rule table according to features to re-encode the siRNA sequence, wherein as the siRNA interference efficiency is further influenced by a sequence and structural characteristics of a target mRNA (Messenger Ribonucleic Acid), the target mRNA is subjected to encoding while the siRNA sequence is encoded; and finally, using the random forest model to forecast the siRNA interference efficiency, during forecasting, using the known sample to establish an optimization model at first, carrying out OOB (out-of-bag) estimation by using OOB data generated by a bootstrap sampling method, enabling the generalization error of the model to be minimum by constantly mediating model parameters, and then using the optimized model to forecast the siRNA interference efficiency.

Description

technical field [0001] The invention belongs to the field of bioinformatics research, and particularly relates to a method for predicting the efficiency of siRNA interference when designing siRNA molecules in RNA interference (RNA interference refers to the phenomenon that double-stranded RNA induces efficient and specific degradation of homologous mRNA). Background technique [0002] RNA interference technology is an effective gene research tool developed in recent years. Its wide application has accelerated the pace of functional genomics research and also promoted research in related fields such as gene therapy. It is one of the key factors affecting the efficiency of RNA interference It is the design of siRNA sequence (siRNA sequence is a string of characters with a length of 19 or 21 composed of four bases, A, U, G, and C). RNA interference technology requires a strict match between the siRNA sequence and the mRNA sequence at the target site, and a single base mismatch ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/18
Inventor 刘元宁张浩段云娜常亚萍张晓旭韩烨
Owner JILIN UNIV
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