Demo Data from SIGIR 2026 / reviewers in the wild / expert
James Bradbury 0001
dblp:160/3382-1
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2015
—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
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
metabolomics |
0.2 | 1 | 2015 | MUSCLE: automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis · Bioinform. 2015 |
Bioinformatics and computational biology
multi-objective optimization |
0.2 | 1 | 2015 | MUSCLE: automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis · Bioinform. 2015 |
Methods — techniques the papers use, named apart from their topics
multi-objective evolutionary optimization · 0.2closed-loop experimentation · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | MUSCLE: automated multi-objective evolutionary optimization of targeted LC-MS/MS analysisabstractAbstract Summary: Developing liquid chromatography tandem mass spectrometry (LC-MS/MS) analyses of (bio)chemicals is both time consuming and challenging, largely because of the large number of LC and MS instrument parameters that need to be optimized. This bottleneck significantly impedes our ability to establish new (bio)analytical methods in fields such as pharmacology, metabolomics and pesticide research. We report the development of a multi-platform, user-friendly software tool MUSCLE (multi-platform unbiased optimization of spectrometry via closed-loop experimentation) for the robust and fully automated multi-objective optimization of targeted LC-MS/MS analysis. MUSCLE shortened the analysis times and increased the analytical sensitivities of targeted metabolite analysis, which was demonstrated on two different manufacturer’s LC-MS/MS instruments. Availability and implementation: Available at http://www.muscleproject.org. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online. James Bradbury 0001, Grégory Genta-Jouve, James William Allwood, Warwick B. Dunn, Royston Goodacre, Joshua D. Knowles, Shan He 0001, Mark R. Viant |
Bioinform. | 1 |