A genome-wide, machine learning-guided exploration of the cis-regulatory code involved in neuronal differentiation
Océane Cassan, Julien Raynal, Christophe Vroland, Kayoko Yasuzawa, Tsukasa Kouno, Jen-Chien Chang, Chung-Chau Hon, Jay W. Shin, Masaki Kato, Hazuki Takahashi, Takeya Kasukawa, Tomoe Nobusada, Vincenzo Lagani, Robert Lehmann, Kévin Yauy, , Charles‐Henri Lecellier
The paper develops a machine learning method to identify cis-regulatory element profiles and their sequence features during neuronal differentiation using single-cell ATAC-seq and RNA-seq data.
bioRxiv · May 14, 2025 · PreprintBioinformatics