Patrick Gohl

ModCRE-NN predicts transcription factor DNA-binding motifs by integrating structural and evolutionary data, showing improved performance under low similarity and uncertainty.

ModCRElib is a package for modeling cis-regulatory elements, offering tools for TF-DNA interaction analysis, binding motif prediction, and regulatory complex modeling.

The paper identifies a 127-gene core network in human astrocytes linking aging to neurodegenerative and cardiovascular diseases through proteostasis and stress signaling.

The paper introduces a structure-based learning approach to predict TF binding preferences and model TF regulatory complexes, demonstrating its effectiveness over existing methods in cases of remote homology.