Fig. 1From: A gene regulatory network inference model based on pseudo-siamese networkData processing framework for exploring gene expression in real-world organisms based on the expression data of maize seeds and the regulatory relationships of leaves. Upon preprocessing the gene time expression dataset and the regulatory relationship dataset, we removed the untrusted parts (\(mean\left( Exp \right) <1\) and p-value\(>0.01\)) and sorted the regulatory relationships based on their p-values. We then selected the genes that appeared in the top 500 and 1000 regulatory relationships and identified the credible regulatory relationships among them. Using this approach, we constructed two sub-datasets, called maize-1 and maize-2, which contain the most reliable regulatory relationships among the expressed genesBack to article page