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DNA—the molecule that carries the genetic information of all living organisms—is packaged within cells in a complex manner that allows it to function efficiently. Nucleosomes facilitate DNA compaction and also play a crucial role in regulating gene expression and other biological processes.

A team of scientists led by Dr. Modesto Orozco at IRB Barcelona has developed an advanced computational technique to predict gene architecture through nucleosome position. The method combines experimental approaches with machine learning techniques and signal transmission theory. The study has been published in the journal Nucleic Acids Research.

A predictive model that rivals experimental methods

Over the past few years, scientists have used experimental techniques such as MNase-seq to map nucleosomes. The model developed by Dr. Orozco´s team uses DNA sequence information and physical characteristics not only to reproduce experimental data, but also to predict nucleosome locations more quickly and accurately.

"The precision of our model is comparable with that of the most advanced experimental methods," says Dr. Orozco, head of the Molecular Modelling and Bioinformatics lab at IRB Barcelona and Full Professor at the University of Barcelona.

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