Cancer cell line therapeutic drug prediction method based on multidimensional network

A cancer cell and prediction method technology, which is applied in the field of cancer cell line therapeutic drug prediction and cancer response to drug prediction experiments, can solve the problems that the accuracy of prediction results needs to be improved, and achieve the effect of improving accuracy and reducing the influence of noise

Active Publication Date: 2019-09-13
XIDIAN UNIV
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Problems solved by technology

The advantage of this type of method is to conduct drug response prediction research from the similarity relationship between cancer cell lines and drugs. The disadvan

Method used

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  • Cancer cell line therapeutic drug prediction method based on multidimensional network
  • Cancer cell line therapeutic drug prediction method based on multidimensional network
  • Cancer cell line therapeutic drug prediction method based on multidimensional network

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Embodiment Construction

[0032] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0033] refer to figure 1 , The implementation steps of this example are as follows:

[0034] Step 1, download the data of cancer cell lines and build a cancer cell line similarity network:

[0035] 1a) Construction of cancer cell line gene expression similarity network

[0036] 1a1) This example downloads the gene expression value data of 955 cancer cell lines from the GDSC database, and obtains the gene expression matrix M exp , gene expression matrix M exp There are 955 rows and 17738 columns, where rows represent cancer cell lines and columns represent genes;

[0037] 1a2) From the gene expression matrix M exp The i-th line in gets the gene expression feature vector of the i-th cancer cell line: Where, i=1,2,3,...,955;

[0038] 1a3) From the gene expression matrix M exp The jth line in gets the gene expression feature ve...

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Abstract

The invention discloses a cancer cell line therapeutic drug prediction method based on multidimensional network, which mainly solves the problem that the prior art has low accuracy of cancer cell linetherapeutic drug prediction results. The solution is to download data of n cancer cell lines to construct a similarity network of the cancer cell lines; download data of m drugs to construct a drug similarity network; calculate a low-dimensional eigenvector matrix of the n cancer cell lines by using a diffusion component analysis algorithm in the similarity network of cancer cell lines; calculatea low-dimensional eigenvector matrix of the m drugs by the diffusion component analysis algorithm in the drug similarity network; obtain a logistic regression model of drug response; calculate the score of the sensitivity relationship between the drugs and the cancer cell lines; and judge whether the drug has a therapeutic effect on the cancer cell line by using the score of the sensitivity relationship. The invention improves the accuracy of cancer cell line therapeutic drug prediction results, and can be used for the prediction experiment of the cancer response to the drug.

Description

technical field [0001] The invention belongs to the technical field of bioinformatics, and in particular relates to a method for predicting cancer cell line therapeutic drugs, which can be used for predicting experiments on the response of cancer to drugs. Background technique [0002] Cancer is a complex and heterogeneous disease. Traditional treatment methods that ignore the biomolecular characteristics of cancer patients and only rely on clinical symptoms of cancer patients cannot meet the requirements of modern medical treatment of cancer. At present, the main means of treating cancer is to use molecular targeted drugs to inhibit the development of cancer. Precision medicine advocates targeted therapy. Selecting specific treatment options based on the molecular characteristics of cancer patients is an effective way to improve the efficacy of cancer treatment. Transplant tumors in animals, then apply compounds to animals, and observe the growth and changes of tumors in a...

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Application Information

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IPC IPC(8): G16H70/40G16B20/20G16B20/50G16B25/10
CPCG16H70/40G16B20/20G16B20/50G16B25/10
Inventor 鱼亮周丹丹
Owner XIDIAN UNIV
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