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Disease correlation prediction method based on twin network

A twin network and prediction method technology, applied in the field of biological information, can solve the problem of small disease correlation calculation range, and achieve the effect of overcoming the limitation of disease correlation calculation and expanding the calculation range

Pending Publication Date: 2022-07-29
XIDIAN UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to overcome the deficiencies of the above-mentioned prior art, and propose a disease correlation prediction method based on twin networks, which is used to solve the problem of the existing in the prior art that the disease correlation calculation range is small due to incomplete disease function information technical issues

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  • Disease correlation prediction method based on twin network
  • Disease correlation prediction method based on twin network
  • Disease correlation prediction method based on twin network

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[0025] The present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments. It should be noted that the present invention does not belong to the object of patent right not granted under Article 25 of the Patent Law, and also complies with the second paragraph of Article 2 of the Patent Law. Provisions:

[0026] refer to figure 1 , this example includes the following steps:

[0027] Step 1, get the disease dataset:

[0028] Obtained from MeSH database including M symptoms E={e 1 ,e 2 ,...,e m ,...,e M } and K disease types Y = {y 1 ,y 2 ,...,y k ,...,y K The set of N diseases of } D={d 1 ,d 2 ,...,d n ,...,d N }, where M=385, e m represents the mth symptom, K=24, y k Indicates the kth disease type, N=4268, d n represents the nth disease;

[0029] Step 2, build a training sample set and a test sample set:

[0030] From the data published in the paper titled "Uncovering disease-diseaserelationships...

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Abstract

The invention provides a disease correlation prediction method based on a twin network, which solves the technical problem of small disease correlation calculation range in the prior art, and comprises the following implementation steps of: (1) acquiring a disease data set; (2) constructing a training sample set and a test sample set; (3) constructing symptom features and classification features of the disease; (4) constructing a disease correlation prediction model based on a twin network; (5) carrying out iterative training on the twin network-based disease correlation prediction model C; and (6) obtaining a disease correlation prediction result. According to the method, the calculation range of disease correlation is remarkably expanded, and the method can be used for guiding classification of diseases, inferring pathogenesis of the diseases, repositioning of drugs and research and development of new drugs.

Description

technical field [0001] The invention belongs to the technical field of biological information, and relates to a disease correlation prediction method, in particular to a disease correlation prediction method based on a twin network, which can be used for guiding the classification of diseases, inferring the pathogenesis of diseases, drug relocation and new drug discovery. R&D. Background technique [0002] The clinical phenotypes of different diseases are very different, but diseases with different clinical phenotypes will also have the same therapeutic target protein or the same pathogenic gene, which provides a new perspective for the study of disease mechanism and drug development . Exploring the association between diseases and diseases helps to better understand the state of human diseases from multiple perspectives, and has a certain guiding role in the classification of diseases. In addition, since similar disease pairs have a greater probability of sharing disease-...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B20/00G16H50/50
CPCG16B20/00G16H50/50
Inventor 鱼亮姜晓鑫
Owner XIDIAN UNIV
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