Zhou, PengSpringer, Nathan M.2020-03-122020-03-122020-03-12https://hdl.handle.net/11299/212030These are the processed datasets used to create networks (raw and filtered expression tables) and predicted interactionsRegulation of gene expression is central to many biological processes. Gene regulatory networks (GRNs) link transcription factors (TFs) to their target genes and represent a map of potential transcriptional regulation. A consistent analysis of a large number of public maize transcriptome datasets including >6000 RNA-Seq samples was used to generate 45 co- expression based GRNs that represent potential regulatory relationships between TFs and other genes in different populations of samples (cross-tissue, cross-genotype, tissue-and-genotype, etc). While these networks are all enriched for biologically relevant interactions, different networks capture distinct TF-target associations and biological processes.CC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/gene regulatory networkDatasethttps://doi.org/10.13020/p3g0-3170