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Correlation analysis method for identifying Alzheimer's disease related biomarkers

A correlation analysis and biomarker technology, applied in the field of correlation analysis to identify Alzheimer's disease-related biomarkers, can solve problems such as lack of effective and accurate correlation analysis models

Pending Publication Date: 2021-07-16
SHANGHAI MARITIME UNIVERSITY
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  • Abstract
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Problems solved by technology

Imaging genetics can reveal the link between microgenetics and macroscopic imaging to detect disease biomarkers, but effective and accurate correlation analysis models are lacking

Method used

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  • Correlation analysis method for identifying Alzheimer's disease related biomarkers
  • Correlation analysis method for identifying Alzheimer's disease related biomarkers
  • Correlation analysis method for identifying Alzheimer's disease related biomarkers

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Embodiment Construction

[0031] based on the following Figure 1 to Figure 8 , specifically explain the preferred embodiment of the present invention.

[0032] In this patent, a new method based on joint connectivity sparse non-negative matrix factorization (JCB-SNMF) is proposed, which combines structural magnetic resonance imaging (SMRI), single nucleotide polymorphism loci (SNP ) and gene expression data are simultaneously projected into a common feature space, in which heterogeneous variables with large coefficients in the same projection direction form a common module, and the connectivity information and genetic data of each brain region are added as a prior empirical knowledge to identify regions of interest (ROIs), risk SNP loci, and risk genes associated with Alzheimer's disease (AD) patients, patients with early cognitive impairment (MCI).

[0033]NMF is a powerful dimensionality reduction computing framework that can integrate different omics data. NMF can decompose a non-negative matrix ...

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Abstract

A correlation analysis method for identifying Alzheimer's disease related biomarkers comprises the following steps: based on sparse non-negative matrix factorization of joint connectivity, projecting structural magnetic resonance imaging (SMRI), single nucleotide polymorphism (SNP) and gene expression data into a public feature space at the same time; and also adding the connectivity information and genetic data of each region of the brain as priori knowledge to identify a region of interest ROI, risk SNP sites and risk genes associated with Alzheimer's disease patients and early cognitive impairment patients. The method has higher correlation analysis capability and better anti-noise performance and biological interpretation performance.

Description

technical field [0001] The present invention relates to imaging genetics based on Alzheimer's disease research, in particular to a correlation analysis method for identifying Alzheimer's disease-related biomarkers. Background technique [0002] Imaging genetics has been widely used in neurodegenerative diseases to explore the influence of genes on brain structure and function and to use brain imaging to assess the influence of genes on individuals. Recently, imaging genetics has made great progress in studying the pathogenesis of Alzheimer's disease and mining Alzheimer's disease-related biomarkers. Imaging genetics can reveal the link between microgenetics and macroscopic imaging and detect disease biomarkers, but there is a lack of effective and accurate correlation analysis models. Contents of the invention [0003] The purpose of the present invention is to provide a correlation analysis method for identifying Alzheimer's disease-related biomarkers, which has stronger...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B20/20G16B40/00G06K9/32G06T7/00
CPCG16B20/20G16B40/00G06T7/0012G06T2207/10088G06T2207/30016G06V10/25
Inventor 位凯孔薇
Owner SHANGHAI MARITIME UNIVERSITY
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