Sebastian ST Triesch

The paper characterizes plant enhancer activity across multiple species and develops a deep learning model to predict enhancer strength and identify functional motifs.

Helixer, a hybrid convolutional/bLSTM network with a hidden Markov model post-processor, predicts eukaryotic primary gene models from DNA alone, outscoring GenemarkES and AUGUSTUS on most species.

The paper uses single-nuclei RNA sequencing to study Moricandia arvensis, revealing bundle sheath cell-specific expression of photorespiration genes and associated pathways in a C3-C4 intermediate plant.

Predmoter predicts ATAC-seq and ChIP-seq read coverage in plant genomes using DNA sequences, improving efficiency in identifying cis-regulatory elements.

The paper presents de novo genome assemblies and annotations for 19 Brassiceae species to study the evolution of C3-C4 intermediate photosynthesis.