Traditional Chinese medicine (TCM) active ingredient forecasting method excavated on the basis of pathway modes

Abstract

The invention discloses a traditional Chinese medicine (TCM) active ingredient forecasting method excavated on the basis of pathway modes. The traditional Chinese medicine active ingredient forecasting method includes the following steps of collecting data of compound ingredients with Chinese Academy of Sciences (CAS) registry numbers in TCM, collecting associated genes of compounds to form compound-gene associated pairs and sorting the genes according to occurrence frequency of the associated genes to form an associated gene list, setting a threshold value to screen frequent genes to form biological pathway data sets and enable each frequent gene to correspond to one biological pathway data record, excavating the pathway modes for the biological pathway data sets, grading the frequency genes, grading activity of the compounds, and setting threshold values for scores of the genes and scores of the activity of the compounds. The compound-gene associated pairs are screened according to the threshold values. The remaining compounds are reserved. Consequently, active ingredients of the TCM can be forecasted.

Description

technical field [0001] The invention relates to the application field of the computer field in the research of active ingredients of traditional Chinese medicines, in particular to a method for predicting active ingredients of traditional Chinese medicines based on pathway pattern mining. Background technique [0002] Traditional Chinese medicine has a long history of development and has been passed down through ancient records and experience. In recent years, more and more domestic and foreign scholars have begun to pay attention to the research of traditional Chinese medicine. In order to study the mechanism of action of traditional Chinese medicine, it is first necessary to clarify the material basis of traditional Chinese medicine. There are many ingredients in traditional Chinese medicine, and the mechanism of action between ingredients is complex. Often, multiple ingredients work synergistically on multiple gene targets. Finding out the active ingredients of traditio...

AI Technical Summary

Problems solved by technology

However, it is difficult to obtain structural information of all components of traditional Chinese medicine, which limits the limitation of this model

The second category of computational models relates the biological activity of a complex system to the composition of the system, however, there is still a lack of accurate computational models to quantify this relationship

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