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In Methods in molecular biology (Clifton, N.J.)

Plants have developed complex regulatory programs to respond to various environmental stress such as heat, drought, and cold. Systematic understanding of these biological processes depends on robust construction of regulatory networks which encodes interactions between transcription factors and target genes. In this chapter, we present a computational tool ConSReg, which predicts regulatory interactions using ATAC-seq, DAP-seq, and expression data. By using expression data generated under a specific environmental stress, ConSReg can reconstruct an interpretable, weighted, and stress response-specific regulatory network.

Song Qi, Li Song


Machine learning, Plant environment stress, Regulatory network