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A drug recognition method based on biomedical knowledge map reasoning

A biomedical and knowledge graph technology, applied in the field of data mining, can solve problems such as text mining method problems

Active Publication Date: 2019-02-12
DALIAN UNIV OF TECH
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Problems solved by technology

[0007] However, with the rapid development of the biomedical field in recent years, the amount of biomedical literature has increased exponentially, and the massive amount of literature and information has brought difficulties to existing text mining methods.

Method used

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  • A drug recognition method based on biomedical knowledge map reasoning
  • A drug recognition method based on biomedical knowledge map reasoning
  • A drug recognition method based on biomedical knowledge map reasoning

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Embodiment Construction

[0039] The present invention is described below in conjunction with accompanying drawing and specific embodiment:

[0040] figure 1 It is an overall flowchart of a drug identification method based on biomedical knowledge graph reasoning in the present invention. A drug identification method based on biomedical knowledge map reasoning, comprising the following steps:

[0041] S1. Download biomedical text data: use the medical literature retrieval system PubMed to download biomedical literature in the form of time retrieval, and store the full text of the downloaded biomedical literature locally in the form of strings to obtain a biomedical literature database;

[0042] S2. Constructing a biomedical knowledge map: including the following steps:

[0043] a1. Extract the relationship between entities: use the relationship extraction tool SemRep to extract the relationship between biological entities from the biomedical literature database, and store the extracted relationship be...

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Abstract

A drug recognition method based on biomedical knowledge map reasoning comprises the following steps of S1, downloading the biomedical text data; S2 constructing a biomedical knowledge map; S3 constructing a drugs-target-disease relationship data set; S4 using a graph embedding method to learn graph representation; 5 training a drug discovery model based on a long-short memory neural network; S6 performing a drug identification step by using the trained model. The method of the invention is applicable to searching for potential therapeutic drugs for diseases, and is not limited to diseases andtypes of drugs, and has great significance to discover drugs that can be used to treat diseases from the literature.

Description

technical field [0001] The invention relates to the field of data mining methods, in particular to a drug identification method based on biomedical knowledge map reasoning. Background technique [0002] Drug discovery is the core driving force for the development of the pharmaceutical industry and an important demand for social development. At present, there are mainly two types of drug discovery methods, namely high-throughput screening (High-throughput screening, HTS) and computer-aided drug discovery / design (computer-aided drug discovery / design, CADD). However, despite great innovations in drug R&D models and technologies, drug discovery is still a very long and costly process. It takes an average of 14 years to develop a new drug and costs about US$1.8 billion. Therefore, how to improve the efficiency of drug discovery has great theoretical and practical value. [0003] Discovering new drugs from the published biomedical literature is an economical and safe drug discov...

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Application Information

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IPC IPC(8): G06F16/36G06N3/08G16H20/10
CPCG06N3/08G16H20/10
Inventor 杨志豪桑盛田
Owner DALIAN UNIV OF TECH
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