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Time sequence data processing method based on dynamic network diagram analysis

A time series, dynamic network technology, applied in electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as small number of samples, large number of variables, and sparse time points.

Inactive Publication Date: 2016-03-30
DALIAN UNIV OF TECH
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AI Technical Summary

Problems solved by technology

Metabolomics time series data often show the characteristics of small number of samples, large number of variables, and sparse time points. Many classic time series algorithms are not suitable for the study of metabolomics time series data.

Method used

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  • Time sequence data processing method based on dynamic network diagram analysis
  • Time sequence data processing method based on dynamic network diagram analysis
  • Time sequence data processing method based on dynamic network diagram analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0034] Example: Screening of liver disease early warning markers based on serum metabolic profile.

[0035] (1) Collection and pretreatment of rat serum samples.

[0036] Diethylnitrosamine was used to induce progressive carcinogenesis in rats. The discovery set contained 10 rats in the control group and 7 rats in the model group. From week 8 (T 1 ) to week 20 (T 7 ), serum samples were collected every 2 weeks, and a total of 119 serum samples were collected at 7 time points. In addition, this biological experiment also included an independent test set consisting of another 6 model group rats. At the 18th week, the liver tissues of these 6 rats were taken for histological examination to determine whether cancer occurred. Therefore, the test set contains 6 time points and a total of 36 serum samples.

[0037] (2) There are 3 liver diseases in the discovery set (N s = 3), T 1 It is a typical hepatitis stage (H), T 2 to T 4 For the stage of liver cirrhosis, T 5 to T 7...

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Abstract

The present invention provides a time sequence data processing method based on dynamic network diagram analysis. The method comprises: analyzing metabonomics queue data from the perspective of a network; analyzing a correlation among variables; constructing a metabolic network according to a dynamic change of the correlation among the variables; and analyzing and determining warning information of occurrence of diseases (such as a malignant tumor) according to a dynamic concentration change and a change of a network topology structure. The time sequence data processing method based on the dynamic network diagram analysis eliminates a disadvantage that characteristic dynamic change information is ignored when a static analysis method is adopted to process time sequence data of metabonomics. Moreover, compared with an algorithm of focusing on finding a monomolecule marker, in the method provided by the present invention, the change of the correlation among the variables over time is considered, and key turns of diseases are analyzed and determined, thereby facilitating a study on pathogenic mechanisms of diseases, and laying a foundation for early diagnosis and a prognostic study of diseases.

Description

technical field [0001] The invention belongs to the technical field of biological data analysis, and is a new method for processing metabonomics time series data by using dynamic network analysis to determine prospective potential biomarkers of complex diseases (such as liver cancer). Background technique [0002] Liver cancer is one of the common malignant tumors, and its mortality rate ranks second among malignant tumors. On average, about 600,000 people die of liver cancer every year in the world. Liver cancer usually arises from chronic liver disease, most often associated with cirrhosis. Since the occurrence of liver cancer involves complex interactions of many factors (such as heredity, virus and environment, etc.), the pathogenic mechanism is still unclear. The prognosis of liver cancer is poor, and patients are often in the advanced stage of cancer when they are diagnosed. At present, conventional diagnostic techniques for liver cancer include ultrasound, imaging, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/12
CPCG16B5/00
Inventor 林晓惠黄鑫曾珺尹沛源
Owner DALIAN UNIV OF TECH
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