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):

https://github.com/seqan/sharg-parser
https://github.com/seqan/hibf
https://github.com/seqan/seqan3