Scialdone, Antonio (2010) Statistical mechanics of genome regulation: the case of X chromosome inactivation. [Tesi di dottorato] (Unpublished)


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Item Type: Tesi di dottorato
Lingua: English
Title: Statistical mechanics of genome regulation: the case of X chromosome inactivation
Date: 24 November 2010
Number of Pages: 102
Institution: Università degli Studi di Napoli Federico II
Department: Scienze fisiche
Scuola di dottorato: Scienze fisiche
Dottorato: Fisica fondamentale ed applicata
Ciclo di dottorato: 23
Coordinatore del Corso di dottorato:
Date: 24 November 2010
Number of Pages: 102
Uncontrolled Keywords: Statistical Mechanics; genome regulation; X inactivation; DNA spatial architecture; stochastic regulatory mechanisms
Settori scientifico-disciplinari del MIUR: Area 02 - Scienze fisiche > FIS/02 - Fisica teorica, modelli e metodi matematici
Area 02 - Scienze fisiche > FIS/07 - Fisica applicata (a beni culturali, ambientali, biologia e medicina)
Date Deposited: 08 Dec 2010 12:01
Last Modified: 30 Apr 2014 19:43
DOI: 10.6092/UNINA/FEDOA/7951


The aim of my PhD research project was to discover the mechanisms behind X Chromosome Inactivation (XCI) one of the most intriguing issues of the current mammalian Biology. XCI is the process whereby a female mammal cell silences one of its two X chromosomes randomly chosen, to equalize the dosage of X products with respect to males (having just one X). We used theoretical models from Statistical Physics and their massive computer simulations to dissect this chromosome-wide stochastic regulatory process. The importance of these investigations goes beyond the XCI, as the comprehension of this process, can indeed shed light on a whole class of regulatory mechanisms involving the genome. By means of our quantitive models, which already found some important experimental confirmations, we were able to provide a new deeper level of understanding of the underlying physical and molecular mechanisms. Precise predictions are given for many genetic/chemical manipulations and a new generation of experiments can be designed. A close interplay between theory and experiments, was guaranteed in our project by the collaboration with an experimental group from Harvard Medical School, USA.


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