Omics data processing method and device based on a graph neural network, equipment and medium

Abstract

The embodiment of the invention provides an omics data processing method and device based on a graph neural network, equipment and a medium, and relates to the technical fields of medical treatment, artificial intelligence, cloud data and the like. The method comprises the following steps: acquiring first omics data to be processed, wherein the first omics data comprises at least two first omics characteristics; determining a first correlation between different omics features in the at least two first omics features; constructing a first graph structure corresponding to the first omics data based on the at least two first omics features and each first correlation, one node in the first graph structure representing one first omics feature, and a connecting edge in the first graph structurerepresenting the first correlation corresponding to two nodes of the connecting edge; based on the first graph structure, obtaining node features of each node in the first graph structure through a graph neural network; and obtaining a medical analysis result based on the node features of each node. According to the invention, the node features can reflect the correlation among the features, and the obtained result is more accurate.

Description

technical field [0001] The present application relates to technical fields such as medical treatment, artificial intelligence, and cloud data. Specifically, the present application relates to a graph neural network-based omics data processing method, device, equipment, and medium. Background technique [0002] There may be huge differences in gene expression and protein expression in different stages of the human life cycle and different stages of disease development, so omics (genomics, transcriptomics, proteomics and metabolomics, etc.) is a systematic study It is an important tool for biological laws. At the same time, because omics can also reflect the life cycle stage of the body and the development of diseases, omics data play a vital role in medical treatment. [0003] At present, some methods based on statistical methods and machine learning have used omics data for diagnosis, typing and prediction of diseases. However, the idea of ​​statistical methods is focused o...

AI Technical Summary

Problems solved by technology

However, the idea of ​​statistical methods is focused on the analysis of differential proteins, which requires a lot of manual intervention, and cannot get a clear classification or typing boundary line

The machine learning method realizes the prediction of omics data to clinical phenotype by screening disease-related biomarkers (biomarkers), but this method carries out subsequent analysis based on a single biomarker or their random combination, which does not reflect the omics data. The cascade regulation mechanism between the two, the interpretability and prediction accuracy of the final prediction results need to be improved

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