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Massachusetts Institute of Technology

Motifs, binding, and expression : computational studies of transcriptional regulation

Abstract

dc:description.abstract

Organisms must control gene expression in response to developmental, nutritional, or other environmental cues. This process is known as transcriptional regulation and occurs through complex networks of proteins interacting with specific regulatory sites in the genome. Recently, high throughput variations of experimental techniques like transcriptional profiling and chromatin immunoprecipitation have emerged and taken on increasing importance in the study of regulatory processes. Mining these experiments for useful biological information requires methods that can handle large quantities of noisy data and integrate information from disparate experimental sources in a principled manner. Not coincidentally, computational and statistical methods for analyzing these data have increasingly become a focal point of research efforts. In this thesis we address three key challenges in the analysis of genomic sequence, protein localization, and expression data: (1) learning representations of the specific binding interactions that determine connectivity in regulatory networks, (2) developing physically grounded models describing these interactions, and (3) relating binding to its ultimate effect on the expression of regulated genes. To this end, we present several different algorithms and modeling techniques and apply them to real biological data in yeast, mouse, and human. Our results demonstrate the utility of leveraging multiple sources of information for improving motif analyses of chromatin immunoprecipitation data. Phylogenetic conservation information and knowledge of an immunoprecipitated protein's DNA binding domain are both shown to have great value in this context.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2009

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • MacIsaac, Kenzie D. (Kenzie Daniel), 1975-
Advisor dc:contributor.advisor
  • Ernest Fraenkel.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/54220
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/54220

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

MacIsaac, Kenzie D. (Kenzie Daniel), 1975-. Motifs, binding, and expression : computational studies of transcriptional regulation. Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/54220