Fundamental limits and algorithms for sequence reconstruction, alignment, and analysis
Mazooji, Kayvon Amir
Loading…
Permalink
https://hdl.handle.net/2142/129454
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
Language
eng
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.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.
