Erik Arner

This study identifies fast and slow gene expression changes in human blood after acute social stress, revealing distinct immune cell-related transcriptional responses and potential molecular mechanisms linking stress to psychiatric disorders.

xcore is an R package that models transcription factor activity using ChIP-seq signatures and gene expression data, demonstrating improved biological relevance in case studies.

ReFeaFi predicts regulatory elements genome-wide using a two-model approach, achieving good performance across species and identifying disease-associated variants in human regulatory regions.

The paper identifies widespread transcription initiation at microsatellites across species and develops deep learning models to predict STR-associated transcription and its impact on disease variants.

DECCODE identifies small molecules that enhance cell reprogramming and conversion using transcriptional data and drug profiles.

DeepCellState predicts cell type-specific transcriptional states after drug treatment using an autoencoder, showing improved accuracy over baselines and generalizing to new cell types and interventions.

The paper functionally annotates human long non-coding RNAs by systematically knocking down 285 lncRNAs and analyzing molecular phenotypes using CAGE sequencing.

RADICL-seq maps genome-wide RNA-chromatin interactions in intact nuclei, revealing general and cell type-specific patterns of transcript occupancy and the role of transcription in chromatin structure.

C1 CAGE detects transcription start sites and enhancer activity in lung cancer cells, revealing subpopulations with distinct responses to TGF-β and enhancer RNA dynamics.