Vercellone, Francesca (2025) Polymer physics of single-cell chromatin architecture: structural and epigenetic variability. [Tesi di dottorato]
|
Documento PDF
Vercellone_Francesca_38.pdf Visibile a [TBR] Amministratori dell'archivio Download (6MB) | Richiedi una copia |
| Tipologia del documento: | Tesi di dottorato |
|---|---|
| Lingua: | English |
| Titolo: | Polymer physics of single-cell chromatin architecture: structural and epigenetic variability |
| Autori: | Autore Email Vercellone, Francesca francesca.vercellone@unina.it |
| Data: | 9 Dicembre 2025 |
| Numero di pagine: | 110 |
| Istituzione: | Università degli Studi di Napoli Federico II |
| Dottorato: | Computational and quantitative biology |
| Ciclo di dottorato: | 38 |
| Coordinatore del Corso di dottorato: | nome email Ceccarelli, Michele michele.ceccarelli@unina.it |
| Tutor: | nome email Nicodemi, Mario [non definito] |
| Data: | 9 Dicembre 2025 |
| Numero di pagine: | 110 |
| Parole chiave: | chromatin modeling, epigenetics, polymer physics, 3D genomics |
| Settori scientifico-disciplinari del MIUR: | Area 05 - Scienze biologiche > BIO/11 - Biologia molecolare Area 02 - Scienze fisiche > FIS/02 - Fisica teorica, modelli e metodi matematici |
| Informazioni aggiuntive: | TRENTOTTESIMO (38) CICLO |
| Depositato il: | 07 Apr 2026 06:32 |
| Ultima modifica: | 10 Ago 2026 14:13 |
| URI: | https://www.fedoa.unina.it/id/eprint/17079 |
Abstract
The three-dimensional (3D) genome organization plays a fundamental role in regulating gene expression and cellular identity. Advances in chromosome conformation capture technologies, such as Hi-C, have revealed the multiscale architecture of chromatin. However, population-averaged Hi-C data obscure the structural variability that exists across individual cells. Emerging single-cell Hi-C (scHi-C) methods now provide direct access to this variability, but their interpretation remains challenging due to the extreme data sparsity. In this thesis, I apply a polymer physics-based framework to infer 3D chromatin architecture from sparse single-cell Hi-C data, bridging the gap between statistical and mechanistic models of genome organization. Using polymer physics models and computational approaches, I reconstruct 3D structures from both bulk and single-cell Hi-C datasets. When applied to experimental scHi-C data, this framework reveals reproducible folding patterns and enables accurate identification of single-cell structural features. Integrating polymer modeling with epigenomic information further uncovers distinct classes of chromatin domains associated with functionally different states, revealing a connection between structural and epigenetic variability. Overall, this work demonstrates that polymer physics provides a quantitative and interpretable framework to explore 3D genome architecture at single-cell resolution, paving the way for future integration with multi-omics and machine-learning approaches to unravel the physical basis of cellular diversity.
Downloads
Downloads per month over past year
Actions (login required)
![]() |
Modifica documento |


