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Functional network characteristic analysis method based on breast cancer diseases

A functional network and feature analysis technology, applied in the field of disease functional network feature analysis, can solve the problem that the improvement of the survival rate of breast cancer patients did not achieve the expected effect and so on

Inactive Publication Date: 2019-02-22
EAST CHINA NORMAL UNIV
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  • Claims
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Problems solved by technology

However, the improvement of the five-year survival rate of breast cancer patients with molecular targeted therapy has not achieved the expected effect, especially for triple-negative breast cancer patients who lack therapeutic targets

Method used

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  • Functional network characteristic analysis method based on breast cancer diseases
  • Functional network characteristic analysis method based on breast cancer diseases
  • Functional network characteristic analysis method based on breast cancer diseases

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Embodiment Construction

[0069] The present invention will be further elaborated below in conjunction with the accompanying drawings and embodiments. A breast cancer disease functional network feature analysis method, comprising:

[0070] 1. Drug-disease network relationship prediction related to breast cancer

[0071] In recent years, the discovery of new uses of existing drugs, that is, drug repositioning research, has become a new direction of drug research and development. The present invention starts from the perspective of drug-disease network relationship mining, combines the network path addition method and path subtraction method proposed by the present invention, and utilizes the known drug-disease interaction relationship to predict the relationship between drugs and diseases .

[0072] 1.1 Dataset construction

[0073] The present invention first obtains 42 drugs related to breast cancer in the KEGG database, and these 42 drugs have 261 drug-disease interaction relationships with 52 dis...

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Abstract

The invention provides a functional network characteristic analysis method based on breast cancer diseases. The method comprises the following steps: step one, integrating various relationship networks including a drug-disease network, a drug-drug network, a drug-target network, and a target-target network and carrying out a series of network topology structure analyses on the networks; step two,on the basis of the e topological structure relation of breast cancer functional networks, digging 11 kinds of pieces of characteristic information capable of describing the drug-target mutual interaction relationship; and step three developing a related breast cancer functional network feature extraction tool. According to the invention, a functional network analysis method for characteristics ofbreast cancer diseases is established to solve a problem of relocation of the drugs; and the potential targets and new drug uses are predicted by using the method, so that the good prediction effectis obtained.

Description

technical field [0001] The invention belongs to the technical field of disease function network feature analysis, and relates to a breast cancer disease function network feature analysis method and its biological application. Background technique [0002] Drug targets usually refer to biomacromolecules that are related to specific diseases or pathological conditions and can be acted on by drugs in vivo. Discovering and validating new drug targets is the first step in drug development, and it is also one of the main bottlenecks in the process of new drug creation. However, the existing research results show that there are less than 500 drug targets successfully developed on the market. With the completion of the Human Genome Project, more and more potential candidate drug targets are expected to be discovered. It is particularly important to elucidate the interaction between drugs and disease target proteins for the discovery of new drug targets and the elucidation of the me...

Claims

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Application Information

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IPC IPC(8): G16H70/40G16H50/70
CPCG16H50/70G16H70/40
Inventor 江振然陶然
Owner EAST CHINA NORMAL UNIV
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