Predicting method of RNA two-grade structure

Abstract

The invention discloses a predicting method of an RNA two-grade structure. The method comprises the steps of performing data preprocessing on a PDB data set, dividing the PDB data set into an RNA first-grade sequence data set and an RNA second-grade structure data set; performing computer coding processing on the RNA first-grade sequence in the RNA first-grade sequence data set, and inputting thecoded RNA first-grade sequence as a characteristic into a machine learning model which is established based on a supervising learning algorithm, obtaining a target function, and using the RNA second-grade structure data set as an output label of the machine learning model, and training and testing the machine learning model; and finally performing RNA two-grade structure predicting by means of thetrained and tested machine learning model. According to the predicting method, a supervising learning algorithm is used and an artificial intelligence method is used for predicting the RNA two-gradestructure, thereby greatly improving predicting efficiency and realizing relatively high predicting result accuracy.

Description

technical field [0001] The invention relates to the field of biological research, in particular to a method for predicting an RNA secondary structure. Background technique [0002] Ribonucleotide molecule RNA, as a macromolecule in organisms, is an important substance existing in organisms. It not only cooperates with deoxyribonucleotide molecules DNA and proteins to maintain the activities of organisms, but also in Plays an important role in DNA and protein synthesis. Studies have found that the study of RNA structure can help us understand the function of RNA molecules more comprehensively, which is beneficial for biological researchers to explore the relationship between RNA, DNA and proteins, so as to understand the function of organisms and understand and treat diseases. [0003] The molecular structure of RNA consists of three parts: primary sequence, secondary structure, and tertiary space structure. The tertiary space structure of RNA is a stable structure formed i...

AI Technical Summary

Problems solved by technology

However, the RNA molecule itself has the characteristics of difficult to obtain crystals and fast molecular degradation, so it is relatively time-consuming and costly to predict its secondary structure by experimental physics and chemical experiments.

The use of computers based on comparative sequence analysis and minimum free energy methods to predict these spatial structures has improved the efficiency of prediction compared with traditional methods, but for secondary structures with long RNA primary sequence bases, the predicted The time and cost are also greatly increased

Images