MiRNA-disease association prediction method and device based on graph neural network fusion multi-view information

A neural network and multi-view technology, applied in the field of biological artificial intelligence, can solve problems such as inability to make full use of multi-omics data, low prediction accuracy, and difficulty in capturing the nonlinear relationship between miRNA and disease

Active Publication Date: 2021-05-11
HUNAN UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to provide a miRNA-disease association prediction method and device based on graph neural network fusion of multi-view information, aiming at combining graph neural network and multi-view learning to solve the problem of ...

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  • MiRNA-disease association prediction method and device based on graph neural network fusion multi-view information

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[0096] In order to describe the purpose, technology and features of the present invention more clearly, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0097] In the specific embodiment of the present invention, the public data set is selected as a sample, and the technical solution of the present invention is evaluated by the method of ten times of five-fold cross-validation.

[0098] figure 1 The overall frame diagram of the model is shown, which is divided into two parts: the miRNA module and the disease module. The internal structure of the two modules is the same. The miRNA module outputs the global features of miRNA, and the disease module outputs the global features of diseases, and the learned miRNA features and disease features are multiplied to reconstruct the correlation matrix.

[0099] A miRNA-disease association prediction method based on graph neural network fusion of multi-...

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Abstract

The invention discloses a miRNA-disease association prediction method and device based on graph neural network fusion multi-view information, and the method integrates miRNA-disease-related multi-omics data to construct a plurality of views, not only considers a plurality of homogeneous similarity networks, but also considers a heterogeneous bipartite network, extracts node features on all views in combination with a graph neural network and multi-view learning, captures dependency between global features and local features through a discriminator, and can better capture the complex nonlinear relation between miRNA and diseases.

Description

technical field [0001] The present invention relates to the field of biological artificial intelligence, in particular to a miRNA-disease association prediction method and device based on graph neural network fusion of multi-view information. Background technique [0002] MicroRNA (miRNA) is an important class of small non-coding RNA molecules that regulate gene expression by degrading mRNA or inhibiting mRNA translation. Accumulating evidence shows that miRNAs play crucial roles in various cancer-related pathways. Therefore, identifying miRNA-disease associations may provide new directions for understanding the underlying pathogenic mechanisms of diseases. [0003] Using biological experiments to identify miRNA-disease associations usually has a high accuracy rate, but it requires a lot of resources and time. In recent years, with the emergence and development of the Human Genome Project and high-throughput sequencing technology, various biological omics data have grown e...

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Application Information

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IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/22G06F18/25Y02A90/10
Inventor 骆嘉伟阳飞蔡洁
Owner HUNAN UNIV
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