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The outbreak of new coronavirus in 2020, the development of bioinformatics technology has become a new hot spot, in which the prediction of protein function module has become a research hotspot. The existing algorithms for predicting protein functional modules have the disadvantages of low accuracy and few functional modules. In this paper, an algorithm for deep learning and PPI network prediction of protein functional modules is proposed. Firstly, three important attributes of PPI network (node location, PPI network structure and core node) are integrated. Then the improved density algorithm is used for clustering analysis, and then the improved isometric mapping dimension reduction algorithm is used for principal component analysis. Finally, MLP is used for training The protein function module was obtained. The accuracy, F value, dimensionality reduction rate and the number of protein functional modules were compared among the other three PPI network based algorithms acc-fmd, MCL and mcode. The experimental results show that IIMP algorithm is better than other algorithms in accuracy, F value, dimension reduction rate and number of recognition modules.

Protein function module of deep learning and PPI network prediction