Statistical analysis and modeling of nucleosome positioning

Jin, Hu

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https://hdl.handle.net/2142/100991 Copy

Description

Title

Statistical analysis and modeling of nucleosome positioning

Author(s)

Jin, Hu

Issue Date

2018-04-16

Director of Research (if dissertation) or Advisor (if thesis)

Song, Jun S.

Doctoral Committee Chair(s)

Aksimentiev, Aleksei

Committee Member(s)

• Kuhlman, Thomas E.
• Kuehn, Seppe

Department of Study

Physics

Discipline

Physics

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Nucleosome
• Nucleosome positioning
• Nucleosome occupancy
• DNA sequence
• Statistical mechanics
• Chromatin
• Cross-entropy
• 10-bp periodicity

Abstract

Nucleosome is the fundamental building block of eukaryotic chromatin. The precise location of nucleosome along the genome plays a central role in gene regulation by controlling the accessibility of genetic information encoded in DNA. Understanding the principles underlying the establishment of genome-wide nucleosome landscape is a critical step towards understanding chromatin structure and diverse cellular processes taking place on the chromatin template. Recent studies have identified various factors that impact the nucleosome landscape in vivo, such as DNA sequence, statistical positioning, and chromatin remodelers; but the results remain largely unconnected and sometimes even provide conflicting views. A comprehensive study integrating different determinants of nucleosome landscape into one consistent framework is still missing. Taking advantage of the flourishing experimental data generated by high-throughput sequencing technology, this thesis applies novel statistical analysis methods and statistical mechanics modeling to the nucleosome positioning problem. We start from quantifying the extent of DNA-encoded sequence signatures and characterizing their respective contributions to different aspects of nucleosome landscape. We then integrate multiple determinants of nucleosome landscape into a unified computational framework and investigate how different factors work together to accurately regulate nucleosome organization.

Graduation Semester

2018-05

Type of Resource

text

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http://hdl.handle.net/2142/100991

Copyright and License Information

Copyright 2018 Hu Jin

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