An integrated machine-learning model to predict nucleosome architecture.

We demonstrate that nucleosomes placed in the gene body can be accurately located from signal decay theory assuming two emitters located at the beginning and at the end of genes. These generated wave signals can be in phase (leading to well defined nucleosome arrays) or in antiphase (leading to fuzzy nucleosome architectures). We found that the first (+1) and the last (-last) nucleosomes are contiguous to regions signaled by transcription factor binding sites and unusual DNA physical properties that hinder nucleosome wrapping.

Nucleosome Dynamics: a new tool for the dynamic analysis of nucleosome positioning.

We present Nucleosome Dynamics, a suite of programs integrated into a virtual research environment and created to define nucleosome architecture and dynamics from noisy experimental data. The package allows both the definition of nucleosome architectures and the detection of changes in nucleosomal organization due to changes in cellular conditions. Results are displayed in the context of genomic information thanks to different visualizers and browsers, allowing the user a holistic, multidimensional view of the genome/transcriptome.