Minimizer-space computation
Name
ekim-ekimb-phd-eecs-2025-thesis.pdf
Description
Thesis PDF
Size
5.6 MB
Format
Adobe PDF
Checksum (MD5)
7e9138812bebd5659d7cfde777b76ff6
Author(s)
Ekim, Barış C.
Advisor(s)
Berger, Bonnie
Date Issued
May 2025
Publisher
Massachusetts Institute of Technology
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.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
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