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MiRNA-disease association prediction method and system based on tensor decomposition

A technology of tensor decomposition and prediction method, applied in the field of bioinformatics, to achieve the effect of good prediction performance

Pending Publication Date: 2021-06-11
HUNAN UNIV
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  • Application Information

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Problems solved by technology

Currently, there is a lack of efficient tensor decomposition-based methods to identify potential miRNA-disease associations

Method used

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  • MiRNA-disease association prediction method and system based on tensor decomposition
  • MiRNA-disease association prediction method and system based on tensor decomposition
  • MiRNA-disease association prediction method and system based on tensor decomposition

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Embodiment Construction

[0068] The scheme of the present invention will be further described below in conjunction with examples and accompanying drawings.

[0069] Such as figure 1 As shown, a tensor decomposition-based miRNA-disease association prediction method includes the following steps:

[0070] Step 1: Construct miRNA-gene-disease association tensor based on known miRNA-disease association data, miRNA-gene association data and gene-disease association data;

[0071] Download the miRNA-disease association data from the HMDD database, download the miRNA-gene association data from the miRNATarBase database, and download the gene-disease association data from DisGeNet.

[0072] Step 1 specifically includes the following steps:

[0073] Step 11: Construct the miRNA-gene-disease association tensor:

[0074] Merge the known miRNA-disease association data, miRNA-gene association data and gene-disease association data to construct the association dataset . Associations are modeled by a rank 3 tenso...

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Abstract

The invention discloses a miRNA-disease association prediction method and system based on tensor decomposition. The method comprises the following steps: using tensors to represent complex relationships among miRNA-disease, miRNA-gene and gene-disease, in the tensor decomposition process, exploring a complex biological mechanism in combination with auxiliary information, then integrating an alternating direction multiplier method (ADMM) framework and an optimization strategy of a conjugate gradient (GC) method to solve an objective function to obtain a miRNA-gene-disease association scoring tensor, converting the association scoring tensor into a miRNA-disease association scoring matrix, and evaluating method performance through the miRNA-disease association scoring matrix so as to provide an effective result for acquiring disease association miRNA. Experiments show that the method provided by the invention has good prediction performance, and can provide an effective result for acquisition of the disease-associated miRNA.

Description

technical field [0001] The invention belongs to the field of bioinformatics of miRNA and disease association prediction, and relates to a tensor decomposition-based miRNA-disease association prediction method and system. Background technique [0002] miRNA is a class of non-coding RNA that plays an important regulatory role in animals by targeting mRNA. In animals, miRNAs are involved in multiple life processes such as cell proliferation, cell differentiation, and cell apoptosis. Studies have shown that miRNA dysfunction has an important relationship with diseases. For example, in human breast cancer samples, the expression of miR-892b will change significantly, and its expression is closely related to the survival of patients. The loss of miR-218 has important effects on the body's muscles. Therefore, the study of disease-associated miRNAs is of great significance for identifying disease biomarkers. Further studies have shown that the dysfunction of miRNA will lead to th...

Claims

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Application Information

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IPC IPC(8): G16B20/00G16B30/00G16B40/00G06F17/16
CPCG16B20/00G16B30/00G16B40/00G06F17/16Y02A90/10
Inventor 骆嘉伟刘祎吴昊
Owner HUNAN UNIV
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