Demo Data from SIGIR 2026 / reviewers in the wild / expert
Birgit Stute
dblp:123/3737
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2013
0000-0003-3118-7966ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1
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 › metabolomics
13c-metabolic flux analysis |
0.2 | 1 | 2013 | 13CFLUX2 - high-performance software suite for 13C-metabolic flux analysis · Bioinform. 2013 |
Bioinformatics and computational biology › metabolomics
metabolic flux analysis |
0.2 | 1 | 2013 | 13CFLUX2 - high-performance software suite for 13C-metabolic flux analysis · Bioinform. 2013 |
High-performance computing
scientific computing systems |
0.2 | 1 | 2013 | 13CFLUX2 - high-performance software suite for 13C-metabolic flux analysis · Bioinform. 2013 |
Methods — techniques the papers use, named apart from their topics
simulation algorithms · 0.3FluxML · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | 13CFLUX2 - high-performance software suite for 13C-metabolic flux analysisabstractSUMMARY: (13)C-based metabolic flux analysis ((13)C-MFA) is the state-of-the-art method to quantitatively determine in vivo metabolic reaction rates in microorganisms. 13CFLUX2 contains all tools for composing flexible computational (13)C-MFA workflows to design and evaluate carbon labeling experiments. A specially developed XML language, FluxML, highly efficient data structures and simulation algorithms achieve a maximum of performance and effectiveness. Support of multicore CPUs, as well as compute clusters, enables scalable investigations. 13CFLUX2 outperforms existing tools in terms of universality, flexibility and built-in features. Therewith, 13CFLUX2 paves the way for next-generation high-resolution (13)C-MFA applications on the large scale. AVAILABILITY AND IMPLEMENTATION: 13CFLUX2 is implemented in C++ (ISO/IEC 14882 standard) with Java and Python add-ons to run under Linux/Unix. A demo version and binaries are available at www.13cflux.net. Michael Weitzel, Katharina Nöh, Tolga Dalman, Sebastian Niedenführ, Birgit Stute, Wolfgang Wiechert |
Bioinform. | 5 |