Fiorillo, Luca (2021) Polymer-physics modeling to explore single-cell DNA architecture and characterize experimental methods. [Tesi di dottorato]

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Item Type: Tesi di dottorato
Resource language: English
Title: Polymer-physics modeling to explore single-cell DNA architecture and characterize experimental methods
Creators:
Creators
Email
Fiorillo, Luca
luca.fiorillo@unina.it
Date: February 2021
Number of Pages: 82
Institution: Università degli Studi di Napoli Federico II
Department: Fisica
Dottorato: Fisica
Ciclo di dottorato: 33
Coordinatore del Corso di dottorato:
nome
email
Capozziello, Salvatore
salvatore.capozziello@unina.it
Tutor:
nome
email
Nicodemi, Mario
UNSPECIFIED
Date: February 2021
Number of Pages: 82
Keywords: DNA; polymer-physics; chromosomes; phase-separation
Settori scientifico-disciplinari del MIUR: Area 02 - Scienze fisiche > FIS/02 - Fisica teorica, modelli e metodi matematici
Date Deposited: 18 Feb 2021 17:07
Last Modified: 07 Jun 2023 10:23
URI: http://www.fedoa.unina.it/id/eprint/14029

Collection description

The comprehension of the spatial organization of chromosomes in mammal cells is a major challenge for contemporary biophysics, as it is connected with the functionality of the genome. For that reason, sophisticated technologies have been designed to explore the chromosomal architectures, while polymer-physics models have been proposed to make sense of the experimental observations and to identify the molecular mechanisms driving the folding of DNA. Here, we present a polymer-physics model which can explain the conformations of DNA observed in human cells, based on the phase-separation mechanism of classical polymers and on the corresponding thermodynamic degeneracy of states. Additionally, we show that model polymer structures of real chromosomal regions can be used to benchmark, computationally, the performances of different experimental technologies able to capture the architecture of chromosomes (Hi-C, GAM and SPRITE). We will illustrate that such approach allows to quantitatively compare the experimental technologies and, so, define the optimal experimental setup for various possible conditions.

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