Demo Data from VLDB 2026 / reviewers in the wild / expert
Michael Predl
dblp:425/2899
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2024
0000-0002-3556-4661ORCID · reported
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% |
Topics — the 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › systems biology
metabolic modeling |
0.8 | 1 | 2024 | PyCoMo: a python package for community metabolic model creation and analysis · Bioinform. 2024 |
Methods — techniques the papers use, named apart from their topics
flux balance analysis · 0.8constraint-based reconstruction and analysis · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | PyCoMo: a python package for community metabolic model creation and analysisabstractSUMMARY: PyCoMo is a python package for quick and easy generation of genome-scale compartmentalized community metabolic models that are compliant with current openCOBRA file formats. The resulting models can be used to predict (i) the maximum growth rate at a given abundance profile, (ii) the feasible community compositions at a given growth rate, and (iii) all exchange metabolites and cross-feeding interactions in a community metabolic model independent of the abundance profile; we demonstrate PyCoMo's capability by analysing methane production in a previously published simplified biogas community metabolic model. AVAILABILITY AND IMPLEMENTATION: PyCoMo is freely available under an MIT licence at http://github.com/univieCUBE/PyCoMo, the Python Package Index, and Zenodo. Michael Predl, Marianne Mießkes, Thomas Rattei, Jürgen Zanghellini |
Bioinform. | 1 |