Abstract
The rapid development of molecular biology and gene chip technology has produced a large amount of gene expression profile data. The main research in this article is to screen the tumor-related genes of gallbladder cancer based on AR-based tumor expression profile gene chip. First, convert the chip data into an expression matrix pattern that can be analyzed, and then standardize and normalize all the data. Run ReliefF, GA, and IReliefF-GA on the data set, record the size of the feature subset, and use the tenfold cross-validation method to obtain the classification accuracy, specificity, and sensitivity of each method on the classifier. The target genes used in the chip were amplified by PCR with the universal primers used in cDNA library construction, and the quality of PCR was monitored by agarose gel electrophoresis. The gene chip data of gallbladder cancer was processed with missing values, singular values, and so forth, and 22294 transcripts were obtained. After statistical testing, there were 9483 transcripts with statistically significant differences. The results show that as the number of clusters increases, the network can be better reconstructed through decomposition modeling.