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A maximum-entropy model for predicting chromatin contacts.

Pau Farré¹, Eldon Emberly¹

¹Department of Physics, Simon Fraser University, Burnaby, BC V5A1S6, Canada.

Plos Computational Biology

|February 6, 2018

Summary

This summary is machine-generated.

This study presents a new computational model to predict DNA structure based on bound factors. The model accurately predicts chromatin folding and can infer DNA-binding sequences from structural data.

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Area of Science:

Genomics
Computational Biology
Molecular Biology

Background:

DNA packaging within the nucleus is a complex structure.
DNA-bound factors stabilize this structure.
Genome-wide measurements of factor distribution and DNA contacts are now possible.

Purpose of the Study:

To develop a model predicting DNA conformation from bound factor locations.
To address the chromatin folding problem using computational methods.

Main Methods:

Developed a maximum-entropy model.
Model predicts DNA contact maps from sequences of bound factors.

Main Results:

The model accurately predicts DNA structure.
Non-local sequence neighborhood effects are crucial for accurate predictions.
The model can infer bound factor sequences from structural data.

Conclusions:

This computational model advances the understanding of chromatin folding.
It enables prediction of DNA-binding sequences and cell-type specific structural variations.