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Algorithms and Data Structures for Population Scale Genomics
Last Updated: 2026-06-01 11:30:51
Abstract
Research in Biology and Medicine have been transformed into disciplines of applied data science over the past years. Not only size and inherent complexity of the data but also requirements on data privacy and complexity of search and access pose a wealth of new research questions.
Objective
This interactive course will explore the latest research on algorithms and data structures for population scale genomics applications and give insights into both the technical basis as well as the domain questions motivating it.
Content
Over the duration of the semester, the course will cover three main topics. Each of the topics will consist of 70% lecture content and 30% practical content. Thereby, the practical implementation of the concepts presented in the lecture forms an integral part of the course. 1) Algorithms and data structures for the efficient compression of and search in texts and graphs. Motivated through applications in compressive genomics, the course will cover succinct indexing schemes for strings, trees and general graphs, compression schemes for binary matrices as well as the efficient representation of haplotypes and genomic variants. 2) Stochastic data structures and algorithms for approximate representation of strings and graphs as well as sets in general. This includes winnowing schemes and minimizers, sketching techniques, (minimal perfect) hashing, approximate membership query data structures, and approximate counting. 3) Data structures supporting encryption and data privacy. As an extension to data structures discussed in the earlier topics, this will include secure indexing using homomorphic encryption as well as design for secure storage and distribution of data.
General Information
- Language
- English
- Levels
- MSC
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- oral 20 minutes
Registration & Places
- Max Places
- 30
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise | Algorithms and Data Structures for Population Scale Genomics |
|
2 h weekly |
Offered In
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Computational Biology and Bioinformatics Master (Weitere Informationen: )
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Vertiefungsfächer (In den Vertiefungsfächern müssen insgesamt 30 ECTS erworben werden. Davon mindestens 16 ECTS in der Unterkategorie Theorie und mindestens 10 ECTS in der Unterkategorie Biologie.)
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Theorie (Mindestens 16 ECTS müssen in dieser Unterkategorie erworben werden.)
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