Sabrina Krueger

The paper maps and interprets low-affinity transcription factor motifs in mESCs, showing they enhance chromatin accessibility and regulatory potential through cooperative interactions.

The paper uses interpretable deep learning to identify sequence rules governing Hippo signaling in mouse trophoblast stem cells, revealing how transcription factors influence enhancer activity.

The paper uses deep learning to analyze chromatin accessibility in Drosophila embryos, revealing a two-phase process driven by pioneer TFs and enhancer-activating TFs.

The paper introduces BPNet, a deep learning model that predicts base-resolution ChIP-nexus binding profiles of TFs and identifies soft syntax rules for cooperative TF binding.