University of Illinois Urbana-Champaign

Analysis of combinatorial gene regulation with thermodynamic models

Chen, Chieh-Chun

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1_Chen_Chieh-Chun.pdf

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https://hdl.handle.net/2142/14656

Description

Title
Analysis of combinatorial gene regulation with thermodynamic models
Author(s)
Chen, Chieh-Chun
Issue Date
2010-01-06T16:20:36Z
Director of Research (if dissertation) or Advisor (if thesis)
Zhong, Sheng
Doctoral Committee Chair(s)
Zhong, Sheng
Department of Study
Bioengineering
Discipline
Bioengineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2010-01-06T16:20:36Z
Keyword(s)
  • Gene Regulation
  • Gene Regulatory Network
Abstract
Transcriptional control is a key regulatory mechanism for cells to direct their destinies. A large number of transcription factors (TFs) could simultaneously bind to a regulatory sequence. With the constellation of TFs bound, the expression level of a target gene is usually determined by the combinatorial control of a number of TFs. The interactions among regulatory proteins and their regulatory sequences collectively form a regulatory network. A major challenge in the study of gene regulation is to identify the interaction relationships within a regulatory network and further to reconstruct gene regulatory networks. In this thesis, we developed an analytical method, Interaction-Identifier, to identify a thermodynamic model that best describes the form of TF-TF interaction among a set of TFs for every target gene. Applying this approach to time-course microarray data in mouse embryonic stem cells, we have inferred five interaction patterns among three regulators: Oct4, Sox2 and Nanog on ten target genes. We further proposed a computational framework, Network-Identifier, utilizing Interaction-Identifier, to reconstruct gene regulatory networks. Applied to five datasets of differentiating embryonic stem cells, Network-Identifier identified a gene regulatory network among 87 transcription regulator genes. This network suggests that Oct4, Sox2 and Klf4 indirectly repress lineage specific differentiation genes by activating transcriptional repressors of Ctbp2, Rest and Mtf2.
Graduation Semester
2009-12
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http://hdl.handle.net/2142/14656
Copyright and License Information
Copyright 2009 Chieh-Chun Chen

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