Home/ Publications/ A convolutional neural network for predicting transcriptional regulators of genes in Arabidopsis transcriptome data reveals classification based on positive regulatory interactions A convolutional neural network for predicting transcriptional regulators of genes in Arabidopsis transcriptome data reveals classification based on positive regulatory interactions Published: 14.05.19 Authors: MacLean D (2019) Reference: bioRxiv preprint Apr 28, 2019 doi: https://doi.org/10.1101/618926 Recent publications See all Published: 27.10.26 Recognition-dependent activation of the Arabidopsis RRS1-R/RPS4 TIR-NLR immune receptor pair Published: 16.10.26 A Blast Fungus Effector Targets a Tubby-like F-box Protein to Suppress Plant Immunity Published: 15.10.26 A broad-host-range Rhizobium rhizogenes strain enables transient expression across diverse crop species
Published: 27.10.26 Recognition-dependent activation of the Arabidopsis RRS1-R/RPS4 TIR-NLR immune receptor pair
Published: 16.10.26 A Blast Fungus Effector Targets a Tubby-like F-box Protein to Suppress Plant Immunity
Published: 15.10.26 A broad-host-range Rhizobium rhizogenes strain enables transient expression across diverse crop species