Organizational overlapping core drug group discovery method based on complex network community discovery

A technology of community discovery and complex network, applied in the field of hierarchical overlapping core drug group discovery
CN102682162AInactive Publication Date: 2012-09-19HOHAI UNIV
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
HOHAI UNIV
Publication Date
2012-09-19
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention provides an organizational overlapping core drug group discovery method based on complex network community discovery, which comprises the following steps: 1) the construction of a traditional Chinese medical formula (TCMF) network: a) the appear contribution (AC) of each drug in a given amount of formula is calculated, and the drugs of which the AC is smaller than a certain threshold value are deleted; b) AC values of two-tuple components are calculated to be cut, and then AC values of triple drugs are calculated to be cut; c) the TCMF network is constructed by using the rest triple drugs; d) the step 1) is completed; and 2) organizational overlapping core drug group discovery of the TCMF network: a) the TCMF network obtained in the step 1) is pre-processed; b) a max clique growing algorithm (MAIGA) is executed on the pre-processed TCMF network, so as to discover drug groups; c) a drug group division result is returned; and d) the step 2) is completed. The organizational overlapping core drug group discovery method explores the compatibility law of the TCMF a viewpoint of complex network, provides a new model for the research of TCMF mining, and solves the problem of traditional single distribution of a cluster.
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Description

technical field

[0001] The invention relates to a method for constructing a traditional Chinese medicine formula (TCMF) network and a method for discovering a layered overlapping core medicine group applicable to the TCMF network. Background technique

[0002] At present, there are three main modes of research on the compatibility of prescriptions using data mining technology: classification-based data mining research mode, cluster-based data mining research mode and association rule mining-based research mode. These three models mostly focus on the analysis of local information such as drug pairs, drug groups or drug-symptoms, syndrome-symptom correlations, etc., and there are still some deficiencies in revealing the "complexity" of the theoretical system of traditional Chinese medicine and the "implicitness" of prescription compatibility laws. For example, the data mining research model based on clustering is difficult to solve the single assignment problem of drug (or pre...

Claims

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