Back to results

Massachusetts Institute of Technology

Unfolding genome organization in interphase

Abstract

dc:description.abstract

Genomic contact frequency maps obtained from high throughput chromosome conformation capture technologies have revealed several organizing patterns of mammalian interphase chromosomes, including self-interacting topologically associating domains (TADs) which are believed to function as coherent gene regulatory neighborhoods. However, the mechanisms driving these patterns are still unknown. In this thesis, I describe and apply computational methods that test the predictions of a recently proposed loop extrusion model in the context of experimental perturbations of its key molecular players. In the first project I introduce a new data model, file format, and supporting software package to cope with the challenges of the increasing size and resolution of Hi-C datasets, including a parallel and scalable matrix balancing implementation.

Degree

thesis:*
Name thesis:degree_name
Doctoral
Department dc:contributor.department
Massachusetts Institute of Technology. Computational and Systems Biology Program
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Abdennur, Nezar Alexander
Advisor dc:contributor.advisor
  • Leonid Mirny.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/122537
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/122537

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Abdennur, Nezar Alexander. Unfolding genome organization in interphase. Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122537