2026-09-23T06:56:56Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/129454 2025-10-20 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

application/pdf en text Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms The student, Kayvon Mazooji, accepted the attached license on 2025-04-26 at 19:32. The student, Kayvon Mazooji, submitted this Dissertation for approval on 2025-04-28 at 02:57. This Dissertation was approved for publication on 2025-05-01 at 11:22. DSpace SAF Submission Ingestion Package generated from Vireo submission #22011 on 2025-10-19 at 18:19:21 Fundamental limits and algorithms for sequence reconstruction, alignment, and analysis Mazooji, Kayvon Amir 2025-05-01 Shomorony, Ilan Shomorony, Ilan Milenkovic, Olgica Raginsky, Maxim Zhao, Zhizhen information theory statistics algorithms computational biology eng 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. 2025-05 Thesis https://hdl.handle.net/2142/129454 Copyright 2025 Kayvon Amir Mazooji Electrical & Computer Eng Electrical & Computer Engr University of Illinois Urbana-Champaign Ph.D. Dissertation