An RNA-Seq Description Method Fused with Local and Global Features

Abstract

The invention provides an RNA sequence description method that combines local and global features, constructs an RNA sequence physicochemical matrix PCM by combining nucleotide duplex structure information and other physical and chemical properties, and the matrix contains RNA sequence structure information and sequence order information. By establishing a gray model for each row of data in the matrix and calculating its autocorrelation factor and cross-correlation factor between rows to obtain the local information of the sequence, convert the PCM into a two-dimensional image, and calculate the geometric distance of the image to obtain the global sequence information. Combining the obtained factors describing sequence local information and global information, a discrete vector description model of RNA sequence is obtained. The method is used in the prediction of RNA attribute types and RNA modification sites, can significantly improve the prediction success rate of related predictors, and has broad application prospects.

Description

technical field [0001] The invention relates to the fields of bioinformatics, RNA sequence pseudonucleotide components and traditional RNA sequence analysis technology, in particular to an RNA sequence description method that combines local and global features. Background technique [0002] With the completion of the sequencing of the human genome, bioinformatics has entered a new stage of development—the post-genome era. The hundreds of millions of genome RNA sequences produced by the Genome Project, RNA sequences are the source of genetic information, how to find out how life originated, how it evolved, how these genes make living organisms active, etc. The answers to a series of questions are the hotspots of current research. As biochemical experiments are time-consuming and laborious, bioinformatics has been greatly developed as a supplement to biological experiments. More and more scholars have explored models for predicting the properties, modification attributes, an...

AI Technical Summary

Problems solved by technology

[0008] The above-mentioned methods are all based on the composition of nucleotides or the physical and chemical properties of nucleotides. It is difficult to determine the starting point of the conversion of RNA into amino acid sequences. Although doublets and triplets contain local information, the global The cha...

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