VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.
Abstract
The category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work.
Objective
Genome analysis is a cornerstone for groundbreaking scientific and medical advancements, including personalized healthcare. However, the field faces significant computational challenges, such as algorithmic bottlenecks and the handling of large datasets. This course aims to provide a comprehensive understanding of these computational facets, spanning across the computing stack from algorithms, software & tools, to microarchitecture & hardware accelerators. The course will cover how advanced hardware solutions like FPGAs and GPUs can expedite genome analysis by reducing computational time and energy consumption. In parallel, it will delve into the use and development of heuristic algorithms & tools for accelerating genome analysis across various computational platforms. These algorithms, for example, can offer tradeoffs between computational intensity and accuracy. Students will engage in hands-on projects focused on optimizing existing methods or innovating new solutions for genome analysis. The curriculum’s dual emphasis on hardware solutions and versatile algorithmic strategies offers students a holistic view of the current challenges and potential resolutions within the realm of genome analysis. Prerequisites of the course: + No prior knowledge in bioinformatics or genome analysis is needed. + An interest in optimizing efficiency and solving complex problems is essential. + Basic to good knowledge in C or C++ programming language is required. + Familiarity with accessing servers using SSH and bash scripting. + Previous coursework in Digital Design and Computer Architecture, or an equivalent course, is desirable. + Experience in either FPGA implementation, GPU programming, or algorithm design is beneficial but not mandatory.
Content
The students carry out a hands-on project under the supervision of their mentors. We also offer the following lectures that the students are encouraged to follow to make impactful progress on their projects. Lecture 1a: P&S Course Introduction & Scope Lecture 1b: Project Overview and Q&A Lecture 2: Introduction to Genome Analysis Lecture 3: From Molecules to Data: An Overview of DNA Sequencing Technologies Lecture 4a: Fundamentals of Sequence Alignment: Algorithms and Applications Lecture 4b: Optimizing Sequence Search: Hashing, Indexing, and Filtering Techniques Lecture 5a: Building the Blueprint of Life: Genome Assembly Lecture 5b: Generating Insights from Genome Analysis: Variant Calling and Functional Genomics Lecture 6a: GateKeeper Lecture 6b: SneakySnake Lecture 6c: GRIM-Filter Lecture 7a: GenASM Lecture 7b: Scrooge Lecture 8: SeGraM Lecture 9: GenStore Lecture 10a: GenPIP Lecture 10b: TargetCall Lecture 11a: BLEND Lecture 11b: AirLift Lecture 12a: Raw Nanopore Signal Analysis & RawHash
Resources
Lecture Notes
See:https://safari.ethz.ch/projects_and_seminars/doku.php?id=bioinformatics
Literature
Learning Materials =============== 1. Overview paper on co-designing hardware and software for genome analysis: https://people.inf.ethz.ch/omutlu/pub/AcceleratingGenomeAnalysis_dac23.pdf 2. Survey on the main steps in the genome analysis pipeline and their bottlenecks: https://people.inf.ethz.ch/omutlu/pub/IntelligentGenomeAnalysis_csbj22.pdf 3. Survey on accelerating genome analysis: https://people.inf.ethz.ch/omutlu/pub/AcceleratingGenomeAnalysis_ieeemicro20.pdf 4. Detailed survey on state-of-the-art algorithms for sequencing data: Link 5. Example of accelerating genomic sequence matching with FPGAs or GPUs: Link 6. Example using different computing paradigms for read mapping and alignment, improving energy consumption: - https://arxiv.org/pdf/1711.01177.pdf - https://arxiv.org/pdf/2208.01243.pdf 7. Examples of software/hardware co-design for genomic sequence matching: - Link - Link - https://people.inf.ethz.ch/omutlu/pub/GenStore_asplos22-arxiv.pdf - https://arxiv.org/pdf/2209.08600.pdf 8. Example on analyzing raw nanopore signals: https://arxiv.org/pdf/2301.09200.pdf
General Information
- Language
- English
- Levels
- BSC
- Frequency
- Semesterly recurring
Examination
- Type
- ungraded semester performance
Registration & Places
- Signup Start
- 13.02.2026
- Signup End
- 27.02.2026
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| practical/laboratory course |
P&S: Accelerating Genome Analysis
Does not take place this semester.
Für den Zugang zum Angebot und zur Einschreibung loggen Sie sich hier ein (mit Ihrem n.ETHZ account):
Bitte beachten Sie, dass die Seite jeweils erst zwei Wochen vor Semesterbeginn zugänglich ist und im Verlauf des Semesters wieder abgeschaltet wird. Die Einschreibung ist nur von Freitag vor Semesterbeginn bis zum ersten Freitagmittag im Semester möglich.
To access the offer and to enroll for courses log in (with your n.ethz account):
Please note that the P&S-site is accessible no earlier than two weeks before the start of the semester until four weeks after the start of the semester. Enrollment is only possible from Friday before the start of the semester until noon of the first Friday in the semester.
Time: to be arranged with each student
Location: various
|
No time listed | 3 h weekly |
Offered In
-
-
Laboratory Courses, Projects, Seminars (A minimum of 15 cp must be achieved in the category "Laboratory Courses, Projects, Seminars")
-
Projects & Seminars (only for BSc EEIT) (Enrolment is only possible for students in the BSc Electrical Engineering and Information Technology, from Friday before the start of the semester. Places are allocated using the P&S application tool ( ). For more offers, see "Projects & Seminars (open to all)".)
-
-