Etienne Routhier

The paper designs synthetic DNA sequences for in vivo nucleosome positioning in yeast using a kinetic Monte Carlo framework combined with deep learning predictions.

This study shows that bacterial chromosomes can undergo chromatin assembly, activity, looping, and compartmentalization in yeast, driven by their sequence composition.

The paper tests if the 601 DNA sequence can position nucleosomes in vivo in yeast, finding that it does not reliably do so in a tandem repeat array context.

This paper trains convolutional neural networks to annotate genomes using sequence data, showing cross-species applicability for transcription start site prediction.