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 [Tesi di dottorato] (Unpublished)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 |
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Resource language: | English |
Title: | Statistical mechanics of genome regulation: the case of X chromosome inactivation |
Creators: | Creators Email Scialdone, Antonio antoscial@gmail.com |
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: | nome email Marrucci, Lorenzo lorenzo.marrucci@na.infn.it |
Tutor: | nome email Nicodemi, Mario mario.nicodemi@na.infn.it |
Date: | 24 November 2010 |
Number of Pages: | 102 |
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 |
URI: | http://www.fedoa.unina.it/id/eprint/7951 |
DOI: | 10.6092/UNINA/FEDOA/7951 |
Collection description
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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