EDBT 2026 Demo / reviewers in the wild / expert
Andrew J. Mikalsen
dblp:367/0058
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2023
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 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% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Storage systems · 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 › metagenomics
metagenomic sequence classification |
0.7 | 1 | 2023 | Coriolis: enabling metagenomic classification on lightweight mobile devices · Bioinform. 2023 |
Storage systems
indexing and storage engines |
0.2 | 1 | 2023 | Coriolis: enabling metagenomic classification on lightweight mobile devices · Bioinform. 2023 |
Methods — techniques the papers use, named apart from their topics
programming model for classifiers · 1.3compact string b-tree · 1.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Coriolis: enabling metagenomic classification on lightweight mobile devicesabstractMOTIVATION: The introduction of portable DNA sequencers such as the Oxford Nanopore Technologies MinION has enabled real-time and in the field DNA sequencing. However, in the field sequencing is actionable only when coupled with in the field DNA classification. This poses new challenges for metagenomic software since mobile deployments are typically in remote locations with limited network connectivity and without access to capable computing devices. RESULTS: We propose new strategies to enable in the field metagenomic classification on mobile devices. We first introduce a programming model for expressing metagenomic classifiers that decomposes the classification process into well-defined and manageable abstractions. The model simplifies resource management in mobile setups and enables rapid prototyping of classification algorithms. Next, we introduce the compact string B-tree, a practical data structure for indexing text in external storage, and we demonstrate its viability as a strategy to deploy massive DNA databases on memory-constrained devices. Finally, we combine both solutions into Coriolis, a metagenomic classifier designed specifically to operate on lightweight mobile devices. Through experiments with actual MinION metagenomic reads and a portable supercomputer-on-a-chip, we show that compared with the state-of-the-art solutions Coriolis offers higher throughput and lower resource consumption without sacrificing quality of classification. AVAILABILITY AND IMPLEMENTATION: Source code and test data are available from http://score-group.org/?id=smarten. Andrew J. Mikalsen, Jaroslaw Zola |
Bioinform. | 1 |