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: 20.08.26 Genomes of Poaceae relatives reveal key metabolic innovations preceding the evolution of grasses Published: 19.08.26 Secondary metabolism in fungal-insect interactions Published: 18.08.26 Iron-responsive transcription factor SreA regulates calcium homeostasis independently of calcineurin-Crz1 pathway in Fusarium graminearum
Published: 20.08.26 Genomes of Poaceae relatives reveal key metabolic innovations preceding the evolution of grasses
Published: 18.08.26 Iron-responsive transcription factor SreA regulates calcium homeostasis independently of calcineurin-Crz1 pathway in Fusarium graminearum