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The essence of technological innovation in the biomedical industry is the classification and evaluation of the technical information in the target domain. This is highly similar to the genetic engineering theory, and the generic technology in the biomedical industry can be regarded as a generic technology gene. In order to identify and extract generic technical information from the biomedical industry and to realize the systematization and visualization of technical gene mapping, thus, deep learning techniques need to be introduced. Based on the method of word vector and deep autoencoder, this paper trains and reduces the dimensionality of a large number of technical text information in China's biomedical industry, and combines cluster analysis to extract generic technology gene information and map the genome. On this basis, the application prospect of deep learning technology in the gene identification of generic technology in general industry is further proposed. [ABSTRACT FROM AUTHOR]