Demo Data from VLDB 2026 / reviewers in the wild / expert
Sylvain Arreckx
dblp:211/7913
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · unresolved
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% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › systems biology › constraint-based modeling
constraint-based reconstruction and analysis |
0.6 | 1 | 2022 | COBREXA.jl: constraint-based reconstruction and exascale analysis · Bioinform. 2022 |
Bioinformatics and computational biology
systems biology |
0.6 | 1 | 2022 | COBREXA.jl: constraint-based reconstruction and exascale analysis · Bioinform. 2022 |
Parallel and multicore computing › parallel computing
parallel scientific computing |
0.6 | 1 | 2022 | COBREXA.jl: constraint-based reconstruction and exascale analysis · Bioinform. 2022 |
Bioinformatics and computational biology › systems biology
metabolic modeling |
0.2 | 1 | 2022 | COBREXA.jl: constraint-based reconstruction and exascale analysis · Bioinform. 2022 |
Methods — techniques the papers use, named apart from their topics
linear programming · 1.1constraint-based modeling · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | COBREXA.jl: constraint-based reconstruction and exascale analysisabstractSUMMARY: COBREXA.jl is a Julia package for scalable, high-performance constraint-based reconstruction and analysis of very large-scale biological models. Its primary purpose is to facilitate the integration of modern high performance computing environments with the processing and analysis of large-scale metabolic models of challenging complexity. We report the architecture of the package, and demonstrate how the design promotes analysis scalability on several use-cases with multi-organism community models. AVAILABILITY AND IMPLEMENTATION: https://doi.org/10.17881/ZKCR-BT30. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Miroslav Kratochvíl, Laurent Heirendt, St. Elmo Wilken, Taneli Pusa, Sylvain Arreckx, Alberto Noronha, Marvin van Aalst, Venkata P. Satagopam, Oliver Ebenhöh, Reinhard Schneider 0002, Christophe Trefois |
Bioinform. | 5 |