2026-09-19T00:43:40Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1640502025-11-26T03:03:41Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Berger, Bonnie
Ekim, Barış C.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2025-11-25T19:38:47Z
2025-11-25T19:38:47Z
2025-05
2025-08-14T19:38:00.242Z
https://hdl.handle.net/1721.1/164050
0000-0002-4040-403X
As the volume of DNA sequencing data increases, the need for algorithmic advances to efficiently handle the data arises. One such concept is minimizers, which are genomic substrings that allow for reduced representations of larger DNA sequences. In this thesis, we introduce minimizer-space computation as a new algorithmic paradigm for DNA sequence analysis. Instead of DNA nucleotides, we consider minimizers as the letters of an extended alphabet in which algorithms operate. We present several techniques on how to efficiently construct these extended alphabets, demonstrate how to develop approaches that use these alphabets and consequently use only a fraction of sequence data, and show how fundamental biological tasks, such as genome assembly and read mapping, can be significantly accelerated over state-of-the-art methods.
Ph.D.
Massachusetts Institute of Technology
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Copyright retained by author(s)
https://creativecommons.org/licenses/by-nc-nd/4.0/
Minimizer-space computation
Thesis
application/pdf
Doctoral
Doctor of Philosophy
Publication
unknown
unknown
<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="b6e51b79-be67-4b76-8599-22e55cdc42f2">
<Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type>
<Title>Minimizer-space computation</Title>
<PublishedIn>
<Publication>
</Publication>
</PublishedIn>
<PublicationDate>2025-05</PublicationDate>
<Authors>
<Author>
<DisplayName>Ekim, Barış C.</DisplayName>
<Affiliation>
<OrgUnit>
</OrgUnit>
</Affiliation>
</Author>
</Authors>
<Editors>
</Editors>
<Publishers>
<Publisher>
<DisplayName>Massachusetts Institute of Technology</DisplayName>
<OrgUnit />
</Publisher>
</Publishers>
<License>https://creativecommons.org/licenses/by-nc-nd/4.0/</License>
<Abstract>As the volume of DNA sequencing data increases, the need for algorithmic advances to efficiently handle the data arises. One such concept is minimizers, which are genomic substrings that allow for reduced representations of larger DNA sequences. In this thesis, we introduce minimizer-space computation as a new algorithmic paradigm for DNA sequence analysis. Instead of DNA nucleotides, we consider minimizers as the letters of an extended alphabet in which algorithms operate. We present several techniques on how to efficiently construct these extended alphabets, demonstrate how to develop approaches that use these alphabets and consequently use only a fraction of sequence data, and show how fundamental biological tasks, such as genome assembly and read mapping, can be significantly accelerated over state-of-the-art methods.</Abstract>
<Access xmlns="http://purl.org/coar/access_right"
>
</Access>
</Publication>