EDBT 2026 Demo / reviewers in the wild / expert
Peter Heringer
dblp:413/3798
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2025
0009-0005-5985-2317ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author · 2 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
High-performance computing · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › comparative genomics › pangenomics
pangenome graph |
0.8 | 1 | 2024 | Cluster-efficient pangenome graph construction with nf-core/pangenome · Bioinform. 2024 |
High-performance computing › cluster computing
cluster deployment |
0.2 | 1 | 2024 | Cluster-efficient pangenome graph construction with nf-core/pangenome · Bioinform. 2024 |
High-performance computing
scientific workflow |
0.2 | 1 | 2024 | Cluster-efficient pangenome graph construction with nf-core/pangenome · Bioinform. 2024 |
Methods — techniques the papers use, named apart from their topics
nextflow · 1.5biocontainers · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Human Readable Compression of GFA Paths Using Grammar-Based CodeabstractInternational audience Peter Heringer, Daniel Doerr |
WABI | 1 |
| 2024 | Cluster-efficient pangenome graph construction with nf-core/pangenomeabstractMOTIVATION: Pangenome graphs offer a comprehensive way of capturing genomic variability across multiple genomes. However, current construction methods often introduce biases, excluding complex sequences or relying on references. The PanGenome Graph Builder (PGGB) addresses these issues. To date, though, there is no state-of-the-art pipeline allowing for easy deployment, efficient and dynamic use of available resources, and scalable usage at the same time. RESULTS: To overcome these limitations, we present nf-core/pangenome, a reference-unbiased approach implemented in Nextflow following nf-core's best practices. Leveraging biocontainers ensures portability and seamless deployment in High-Performance Computing (HPC) environments. Unlike PGGB, nf-core/pangenome distributes alignments across cluster nodes, enabling scalability. Demonstrating its efficiency, we constructed pangenome graphs for 1000 human chromosome 19 haplotypes and 2146 Escherichia coli sequences, achieving a two to threefold speedup compared to PGGB without increasing greenhouse gas emissions. AVAILABILITY AND IMPLEMENTATION: nf-core/pangenome is released under the MIT open-source license, available on GitHub and Zenodo, with documentation accessible at https://nf-co.re/pangenome/docs/usage. Simon Heumos, Michael L. Heuer, Friederike Hanssen, Lukas Heumos, Andrea Guarracino, Peter Heringer, Philipp Ehmele, Pjotr Prins, Erik Garrison, Sven Nahnsen |
Bioinform. | 6 |