EDBT 2026 Demo / reviewers in the wild / expert
Tom Eilers
dblp:424/3632
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
0000-0002-7509-2902ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 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% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
comparative genomics |
0.9 | 1 | 2025 | SCARAP: scalable cross-species comparative genomics of prokaryotes · Bioinform. 2025 |
Bioinformatics and computational biology › genomics › computational genomics
genome subsampling |
0.9 | 1 | 2025 | SCARAP: scalable cross-species comparative genomics of prokaryotes · Bioinform. 2025 |
Methods — techniques the papers use, named apart from their topics
phylogeny inference · 0.9gene fixation frequency · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | SCARAP: scalable cross-species comparative genomics of prokaryotesabstractMOTIVATION: Much of prokaryotic comparative genomics currently relies on two critical computational tasks: pangenome inference and core genome inference. Pangenome inference involves clustering genes from a set of genomes into gene families, enabling genome-wide association studies and evolutionary history analysis. The core genome represents gene families present in nearly all genomes and is required to infer a high-quality phylogeny. For species-level datasets, fast pangenome inference tools have been developed. However, tools applicable to more diverse datasets are currently slow and scale poorly. RESULTS: Here, we introduce SCARAP, a program containing three modules for comparative genomics analyses: a fast and scalable pangenome inference module, a direct core genome inference module, and a module for subsampling representative genomes. When benchmarked against existing tools, the SCARAP pan module proved up to an order of magnitude faster with comparable accuracy. The core module was validated by comparing its result against a core genome extracted from a full pangenome. The sample module demonstrated the rapid sampling of genomes with decreasing novelty. Applied to a dataset of over 31 000 Lactobacillales genomes, SCARAP showcased its ability to derive a representative pangenome. Finally, we applied the novel concept of gene fixation frequency to this pangenome, showing that Lactobacillales genes that are prevalent but rarely fixate in species often encode bacteriophage functions. AVAILABILITY AND IMPLEMENTATION: The SCARAP toolkit is publicly available at https://github.com/swittouck/scarap. Stijn Wittouck, Tom Eilers, Vera van Noort, Sarah Lebeer |
Bioinform. | 2 |