261-5112-00L  Algorithms and Data Structures for Population Scale Genomics

SemesterAutumn Semester 2020
LecturersA. Kahles
Periodicityyearly recurring course
Language of instructionEnglish
CommentNumber of participants limited to 30.



Courses

NumberTitleHoursLecturers
261-5112-00 GAlgorithms and Data Structures for Population Scale Genomics2 hrs
Wed14:15-16:00HG D 3.2 »
A. Kahles

Catalogue data

AbstractResearch in Biology and Medicine have been transformed into disciplines of applied data science over the past years. Not only size and inherentcomplexity of the data but also requirements on data privacy and complexity of search and access pose a wealth of new research questions.
Learning objectiveThis 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.
ContentOver the duration of the semester, the course will cover three main topics. Each of the topics will consist of 70-80% lecture content and 20-30% seminar content.
1) Algorithms and data structures for text and graph compression. 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 and approximate membership query data structures.
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.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits3 credits
ExaminersA. Kahles
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationoral 20 minutes
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

 
Main linkInformation
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Groups

No information on groups available.

Restrictions

Places30 at the most
Waiting listuntil 28.09.2020

Offered in

ProgrammeSectionType
Computational Biology and Bioinformatics MasterTheoryWInformation
Data Science MasterInterdisciplinary ElectivesWInformation