In the absence of a clear molecular understanding of the mechanism that stabilizes specific contacts in interphasic chromatin, we resort to the principle of maximum entropy to build a polymeric model based on the Hi-C data of the specific system one wants to study. The interactions are set by an iterative Monte Carlo algorithm to reproduce the average contacts summarized by the Hi-C map. The study of the ensemble of conformations generated by the algorithm can report a much richer set of information than the experimental map alone, including colocalization of multiple sites, fluctuations of the contacts, and kinetical properties.

Polymer Folding Simulations from Hi-C Data / Y. Zhan, L. Giorgetti, G. Tiana (METHODS IN MOLECULAR BIOLOGY). - In: Hi-C Data Analysis / [a cura di] S. Bicciato, F. Ferrari. - [s.l] : Humana Press Inc., 2022. - ISBN 9781071613894. - pp. 259-265 [10.1007/978-1-0716-1390-0_13]

Polymer Folding Simulations from Hi-C Data

Y. Zhan
Primo
;
L. Giorgetti;G. Tiana
Ultimo
2022

Abstract

In the absence of a clear molecular understanding of the mechanism that stabilizes specific contacts in interphasic chromatin, we resort to the principle of maximum entropy to build a polymeric model based on the Hi-C data of the specific system one wants to study. The interactions are set by an iterative Monte Carlo algorithm to reproduce the average contacts summarized by the Hi-C map. The study of the ensemble of conformations generated by the algorithm can report a much richer set of information than the experimental map alone, including colocalization of multiple sites, fluctuations of the contacts, and kinetical properties.
Data-driven modeling; Polymeric model; Principle of maximum entropy
Settore BIOS-08/A - Biologia molecolare
2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1156662
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