2026-09-21T06:59:31Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/110757 2023-07-11 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Shomorony, Ilan Greenberg, Grant 2021-09-17T02:34:51Z 2021-09-17T02:34:51Z 2023-09-17T02:34:57Z 2021-04-30 2021-05 The goal of metagenomics is to study the composition of microbial communities, typically using high-throughput shotgun sequencing. In the metagenomic binning problem, we observe random substrings (called contigs) from a mixture of genomes and want to cluster them according to their genome of origin. Based on the empirical observation that genomes of different bacterial species can be distinguished based on their tetranucleotide frequencies, we model this task as the problem of clustering N sequences generated by M distinct Markov processes, where M ≪ N. Utilizing the large-deviation principle for Markov processes, we establish the information-theoretic limit for perfect binning. Specifically, we show that the length of the contigs must scale with the inverse of the Chernoff Information between the two most similar species. Our result also implies that contigs should be binned using the conditional relative entropy as a measure of distance, as opposed to the Euclidean distance often used in practice. Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-05-01 The student, Grant Greenberg, accepted the attached license on 2021-04-30 at 09:06. The student, Grant Greenberg, submitted this Thesis for approval on 2021-04-30 at 09:16. This Thesis was approved for publication on 2021-04-30 at 09:32. DSpace SAF Submission Ingestion Package generated from Vireo submission #16620 on 2021-09-16 at 17:06:54 Made available in DSpace on 2021-09-17T02:34:51Z (GMT). No. of bitstreams: 3 GREENBERG-THESIS-2021.pdf: 633746 bytes, checksum: a612ae29970005be421046f59248518a (MD5) thesis.zip: 6622324 bytes, checksum: b921f217f9dc9f2a444f1570727fd8de (MD5) LICENSE.txt: 4212 bytes, checksum: 42b900533609cd690b1aae9f8f13b18f (MD5) Previous issue date: 2021-04-30 Embargo set by: Seth Robbins for item 118600 Lift date: 2023-09-17T02:34:57Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system U of I Only application/pdf http://hdl.handle.net/2142/110757 en Copyright 2021 Grant Greenberg Metagenomics Information Theory Large Deviation Theory Computational Biology Bioinformatics Genomics Information theoretic limits of metagenomic binning text Thesis Electrical & Computer Eng Electrical & Computer Engr University of Illinois at Urbana-Champaign Thesis M.S.