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A method for screening tumor protein markers based on multi-layer complex network

A complex network and protein technology, applied in the field of screening tumor protein markers based on multi-layer complex networks, can solve problems such as failure to learn, difficult to interpret output results, and long learning time for artificial neural network algorithms, and the method is simple and accurate. high degree of effect

Active Publication Date: 2018-09-14
赵毅
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Since the learning process in the middle cannot be observed, the output results are difficult to explain, which will affect the credibility and acceptability of the results, and the artificial neural network algorithm takes a long time to learn, and sometimes it may not even achieve the purpose of learning

Method used

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  • A method for screening tumor protein markers based on multi-layer complex network
  • A method for screening tumor protein markers based on multi-layer complex network
  • A method for screening tumor protein markers based on multi-layer complex network

Examples

Experimental program
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Effect test

Embodiment 1

[0067] The source of the research data is The Cancer Genome Atlas / TCGA (https: / / tcga-data.nci.nih.gov / tcga / dataAccessMatrix.htm). Select the data of invasive breast cancer patient protein Experssion-Protein data level 3 to download. Among them, there are 285 protein data, which come from 937 patients. Among the protein expression data, 45 are normal tissue protein data of breast cancer patients, and the rest are tumor tissue protein data of breast cancer patients. In the protein data of normal tissue and tumor tissue, there are many proteins that are not expressed or the expression rate is low. Remove the individuals that do not express the protein, and obtain the protein data of normal tissue and breast tumor tissue with a size of 137×45, that is, select 137 out of 45 patients. Different types of normal tissue protein data and 137 tumor tissue protein data of the same type as normal tissue.

[0068] The random forest model is used to encapsulate and filter the protein data ...

Embodiment 2

[0077] The protein data of lung cancer patients were downloaded by using the method of Example 1, wherein the protein data were 276 from 166 patients. After deleting the censored data, 137×166 lung cancer tumor tissue protein data are obtained. Since lung cancer patients lack normal tissue data, here we select the normal tissue data of breast cancer patients as a control, that is, select 131 tumor tissue proteins of the same type from 166 patients data and 131 normal tissue protein data from 45 patients.

[0078] The random forest model is used to encapsulate and filter the protein data of normal tissue and tumor tissue of lung cancer patients to select the best subset. In order to select the protein subset with the smallest number of genes and maintain the highest classification accuracy, a ten-fold cross-validation test was used to evaluate the classifier model, and the protein classification results are shown in Table 4. For the breast cancer data set, when the number of p...

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Abstract

The invention provides a method for screening tumor protein markers on the basis of a multilayer complex network. According to the method, node betweennesses of a random forest mode and of a complex network are combined to provide a new visual angle to discover the tumor pathogenic factors and diagnosis markers. Through bioinformatics and mathematic statistical analysis, the correlation of multilayer protein network data is established and a screening method which is more convenient and higher in correctness is disclosed, so that more valuable reference is provided or the cancer diagnosis and drug discovery.

Description

technical field [0001] The invention relates to the technical field of tumor markers, in particular to a method for screening tumor protein markers based on a multi-layer complex network. Background technique [0002] Cancer is one of the major diseases and serious public health problems that seriously threaten human survival and social development. Cancer control has become the health strategy focus of governments around the world. In recent years, there have been more and more studies on proteins. The expression level of proteins is related to the type of cancer, stage and other clinical data of patients, and plays a role in almost all aspects of cancer biology, such as proliferation, apoptosis, invasion, Metastasis and angiogenesis. [0003] When selecting tumor markers, selecting only one serum protein as a tumor marker often has low specificity. If multiple protein combinations or protein expression profiles are measured, the accuracy of diagnosis can be improved. But...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/18G06F19/24
CPCG16B20/00G16B40/00
Inventor 赵毅张阳
Owner 赵毅
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