miRNA-disease association identification method and system based on fusion attributes

Abstract

The invention discloses a miRNA-disease association identification method and system based on fusion attributes. The method comprises the following steps: firstly, calculating functional similarity between any two miRNAs in a disease database, constructing an miRNA network undirected graph according to the functional similarity, calculating an aggregation coefficient between any two different miRNAs, and fusing the functional similarity and the aggregation coefficient between the two miRNAs to obtain a combined weight; secondly, calculating the weight of each miRNA vertex according to the combined weight, performing descending sort on each miRNA according to the weight, and screening out potential miRNAs related to diseases according to a descending sort result. The method is simple to implement; on the basis of fusing two attributes of topology attributes and function similarity, the miRNA nodes are weighted and sequenced in a descending order, and then potential correlation between miRNA and diseases is predicted by means of a disease database related to human miRNA and by means of a sequenced result, so the miRNA-disease correlation identification accuracy is improved, and valuable clues can be provided for medical diagnosis.

Description

technical field [0001] The invention relates to the technical field of information biology, in particular to a method and system for identifying miRNA-disease associations based on fusion attributes. Background technique [0002] miRNAs (microRNAs) are small non-coding RNAs, including about 22 amino acids, which play an important role in the post-transcriptional regulation of gene expression and various biological activities. Studies have demonstrated that the dysfunction of miRNAs is associated with various complex human diseases. Therefore, identifying potential miRNA-disease associations will help to understand pathogenic mechanisms and provide valuable references for medical diagnosis of human diseases. In 2010, Jiang et al. quantified the functional similarity between miRNAs for the first time by using the overlapping degree of target genes of miRNAs, optimized disease-related miRNAs through hypergeometric distribution, and further integrated the phenotypic similarity ...

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Problems solved by technology

[0005] The purpose of the present invention is to provide a miRNA-disease association recognition method and system based on fusion attributes, to predict the potential association between miRNAs and diseases based on topological attributes and functional similarity methods, so as to solve the existing miRNA-disease association The problem of low accuracy of the identification method

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