Fundamental limits and algorithms for sequence reconstruction, alignment, and analysis

Mazooji, Kayvon Amir

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https://hdl.handle.net/2142/129454 Copy

Description

Title

Fundamental limits and algorithms for sequence reconstruction, alignment, and analysis

Author(s)

Mazooji, Kayvon Amir

Issue Date

2025-05-01

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

Shomorony, Ilan

Doctoral Committee Chair(s)

Shomorony, Ilan

Committee Member(s)

• Milenkovic, Olgica
• Raginsky, Maxim
• Zhao, Zhizhen

Department of Study

Electrical & Computer Eng

Discipline

Electrical & Computer Engr

Degree Granting Institution

University of Illinois Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• information theory
• statistics
• algorithms
• computational biology

Abstract

This dissertation studies several problems concerning the reconstruction, alignment, and analysis of sequences. The results obtained are all motivated by or applicable to problems involving biological sequences, e.g. DNA, RNA, and proteins. These applications include privacy-preserving DNA sequencing, the reconstruction of proteins from tandem mass spectrometry data, DNA data storage, phylogeny inference, protein structure and function inference, and the clustering of cells into cell-types based on gene expression. The specific problems studied concern trace reconstruction, multiple sequence alignment, density-based clustering, flow graph decomposition, and information-theoretic privacy. The contributions in this dissertation are theoretical and algorithmic in nature, but applications to real datasets are included in some cases.

Graduation Semester

2025-05

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/129454

Copyright and License Information

Copyright 2025 Kayvon Amir Mazooji

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