Educators:
Enrico Seiler (CIBI), Jonas Schulte-Mattler, Svenja Mehringer
Date:
2026-09-22
Location:
40th German Conference on Bioinformatics, Saarbrücken, Germany
(#GCB2026,https://gcb2026.de/gcb2026_workshops.html#WS09)
Contents:
Exploration of scalable tools for sequence analysis, focusing on Approximate Membership Queries (AMQ) for short sequence patterns in large reference datasets. Application of the Hierarchical Interleaved Bloom Filter (HIBF) to a read mapper.
Learning goals:
- Describe the general concept and key applications of AMQ.
- Apply AMQ to an example read mapper application.
- Compare the performance of the application with and without AMQ.
- Gain hands-on experience with modern C++ API integration.
Prerequisites:
- Fundamental knowledge of sequencing experiments and associated data.
- Intermediate programming skills in a high-level language (e.g., Python, Java, or Rust).
- Basic C++ knowledge (helpful but not mandatory).
- A laptop to connect to the provided virtual machine.
Keywords:
Sequence analysis, genomics, metagenomics, read alignment, Approximate Membership Query (AMQ), Hierarchical Interleaved Bloom Filter (HIBF), C++, indexing data structures
Tools:
de.NBI Cloud
SeqAn (C++20/23):
Contact: