Research On The Learning Technology Of Biological Network Structure Based On Network Embedding Vector

With great progress of biotechnology continuously being made,biological data has exploded and the rapid development of information technology has made it possible to study massive biological data.Research on the biological network abstracted from the complex structure of massive data has gradually become a research hotspot,and there is still a lot of space for the exploration of gut microbial network in the biological field.At present,the main method of gut microbial analysis is the study of microbial diversity and the corresponding function of microbial gene sequence,which lacks the exploration of the complex coupling relationship between gut microbes.In order to study the Interacting complexes in gut microbes,complex network module analysis is introduced to reveal the modular structure of microbial data in this paper.At the same time,in view of the problems of hidden variables,hidden relationships that are difficult to detect and unbalanced network structure in the microbial network,this paper uses the network embedding technology in e-learning to convert the network structure information into embedding vectors,thereby increasing the network feature analysis dimension to solve the above problems.In this paper,by constructing a firstorder microbial network and a high-order microbial embedded network and applying network module analysis,it is confirmed that the method can dig OTU potential information in gut microbial data and make a way for the following extraction of functional modules.The method can also be applied to other biological fields to analyze the structure of complex biological complexes.