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Method for detecting phase change critical point of complex biological system based on single-sample sKLD index

A biological system and critical point technology, applied in the field of phase transition critical point inspection of biological systems, can solve the problems of reduced correlation

Active Publication Date: 2020-04-14
SOUTH CHINA UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0008] 2. The correlation between any one molecule in the dynamic network biomarker panel and any other non-dynamic network biomarker molecules decreases rapidly;

Method used

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  • Method for detecting phase change critical point of complex biological system based on single-sample sKLD index
  • Method for detecting phase change critical point of complex biological system based on single-sample sKLD index
  • Method for detecting phase change critical point of complex biological system based on single-sample sKLD index

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0055] Verification in Numerical Simulation Based on sKLD Index

[0056] Such as figure 1 As shown, the case implemented by the present invention discloses a method for detecting the critical state before the phase transition of a complex biological system based on the sKLD index. according to figure 1 The public schematic diagram of the process, the results obtained in this implementation are as follows:

[0057] 1. Identify the pre-disease state of the eight-node network:

[0058] A model of an eight-node artificial network (Fig. 2(A)) was used to verify the proposed computational method. The network is a regulatory representation of a set of eight biomolecules governed by eight stochastic differential equations.

[0059] In this example, a regulatory network comprising 8 genes (see FIG. 2(A)) is used for numerical simulation to detect critical periods in the development process of biological systems using SKLD. These types of gene molecular regulatory networks are comm...

Embodiment 2

[0070] Application of sKLD-based index in the data set of acute lung injury induced by phosgene inhalation

[0071] The sKLD indicator algorithm has been applied to the microarray data of the (GSE2565) dataset derived from mouse experiments with phosgene-induced acute lung injury. In the original experiment, the gene expression data of the experimental samples were derived from the lung tissues of CD-1 male mice exposed to phosgene for 72 hours, while the gene expression data of the control samples were derived from the lung tissues of CD-1 male mice exposed to air. During the experiment, there were 9 sampling points in the experimental group and the control group, respectively at 0, 0.5, 1, 4, 8, 12, 24, 48 and 72 hours, and 6-8 mice were taken at each sampling point. lung tissue. The samples at the first time point (0 hour) were taken as the reference group samples. As shown in Fig. 3(A), sKLD suddenly increased between 1 and 4 h and reached a peak at 8 h, which indicated ...

Embodiment 3

[0074] Application of sKLD-based indicators in 5 tumor datasets

[0075] To further demonstrate the effectiveness of the method, it was applied to 5 tumor datasets: lung squamous cell carcinoma, lung adenocarcinoma, gastric adenocarcinoma, thyroid cancer, and colon cancer, all of which were obtained from the TCGA Cancer Gene Atlas by Tumor and tumor-adjacent sample composition. According to the corresponding clinical data of TCGA, tumors were divided into different stages. Lung squamous cell carcinoma, lung adenocarcinoma, and gastric adenocarcinoma can be divided into 7 stages, and thyroid cancer and colon cancer can be divided into 4 stages. In all 5 datasets, tumor adjacent samples were used as normal / reference samples. The sKLD of each individual tumor sample was then calculated according to the sKLD algorithm. Finally, the average sKLD of each stage was taken to determine the critical stage of the tumor.

[0076] The sKLD indicator successfully identified critical sta...

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Abstract

The invention discloses a method for detecting a phase change critical point of a complex biological system based on a single sample sKLD index. Rich dynamic information is mined from high-throughputdata, different dynamic characteristics between a normal state and a critical state are utilized, interference of a single sample on reference group sample distribution is quantified, and therefore anearly warning signal of the critical state or phase change is determined. In order to verify the effectiveness of the algorithm, the algorithm is applied to a regulation and control network based onan analog data set and six real data sets, wherein the six real data sets are respectively a data set of a gene expression profile generated by inducing pulmonary edema by inhaling carbonyl chloride in a mouse experiment and a cancer data set of five TCGA databases (lung squamous cell carcinoma, lung adenocarcinoma, gastric adenocarcinoma, thyroid carcinoma and colon cancer).

Description

technical field [0001] The invention relates to the technical field of phase transition critical point inspection of biological systems, in particular to a method for detecting phase transition critical points of complex biological systems based on a single-sample sKLD index. Background technique [0002] The development process of a biological system is usually a nonlinear process with three stages, namely normal state, critical state and disease state, where the critical state is the critical point where the normal state enters the disease state. Traditional biomarkers aim to identify disease states by exploiting observed differential expression information of molecules, but criticality of phase transitions in complex biological systems may not be detected since there is usually no significant difference between normal and critical states. Therefore, it is a challenge to signal early warning of critical states, which actually means predicting phase transition critical poin...

Claims

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Application Information

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IPC IPC(8): G16H10/20G16H50/00
CPCG16H10/20G16H50/00Y02A90/10
Inventor 刘锐钟佳元马硕金海洋陈培
Owner SOUTH CHINA UNIV OF TECH
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