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Metabonomics network marker identification method based on horizontal relation

A network marker and metabolomics technology, applied in the field of biological data analysis, can solve problems such as sample change disturbance, achieve the effect of good discrimination ability and effective data processing means

Active Publication Date: 2019-10-11
DALIAN UNIV OF TECH
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Problems solved by technology

The TSP algorithm provides a simple decision rule, but is susceptible to perturbations by sample changes

Method used

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  • Metabonomics network marker identification method based on horizontal relation
  • Metabonomics network marker identification method based on horizontal relation
  • Metabonomics network marker identification method based on horizontal relation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0028] Example: Screening of potential network markers for breast cancer subtype discrimination based on human metabolism.

[0029] (1) Human Metabolic Breast Cancer Data

[0030] The human metabolic breast cancer dataset used in this example is a public dataset (Jan Budczies, Scarlet F. Berit M.Müller, et al.Comparative metabolomics of estrogen receptor positive and estrogen receptor negative breast cancer: alterations inglutamine and beta-alanine metabolism[J].Journal of Proteomics,2013,94:279-288), including 162 qualitative metabolites There are two categories: estrogen receptor negative (ER-) and estrogen receptor positive (ER+). The data is divided into a training set and a test set. Among them, the training set contains 41 ER- samples and 143 ER+ samples. The test set contains 26 ER- samples and 61 ER+ samples.

[0031] (2) Build a horizontal relationship network on each type of sample in the training set

[0032] (2.1) Build a horizontal relationship network on ER...

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Abstract

The invention provides a metabonomics network marker identification method based on a horizontal relation, belongs to the technical field of biological data analysis, and relates to a metabonomics data analysis method DNB-HC for screening potential network markers of complex diseases. The horizontal relation between the features is defined by using probability scores and is used for measuring thesize relation of the relative expression levels of a pair of metabolic features in the same sample, and the robustness of the horizontal relation is determined through a random disturbance test, so that the network connection edge is determined. Besides, the network markers are identified by using a difference network analysis method, and the screened network metabolic markers have relatively gooddistinguishing capability, so that a practical and effective data processing means can be provided for researching a disease occurrence and development mechanism and diagnosing diseases.

Description

technical field [0001] The invention belongs to the technical field of biological data analysis, uses feature-level relationships to construct a network, analyzes metabolomics data, and is used to identify potential network markers of complex diseases (such as malignant tumors). Background technique [0002] Metabolomics is an important part of systems biology, and its research objects are small molecular substances with a relative molecular mass of less than 1000. Through the qualitative and quantitative analysis of metabolites in organisms, the change rules of metabolites in physiological and pathological processes can be mined to reflect the current physiological state of the body. Compared with biological molecules such as genes and proteins, metabolites are at the end of the regulation of life activities and can directly reflect the biochemical activities in the metabolic process. Therefore, metabolomics has been widely used in the discovery of clinical markers, early d...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B40/00G16B5/20
CPCG16B5/20G16B40/00
Inventor 林晓惠苏本哲黄鑫
Owner DALIAN UNIV OF TECH
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