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James Bradbury 0001

dblp:160/3382-1 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
metabolomics
0.212015
MUSCLE: automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis · Bioinform. 2015
Bioinformatics and computational biology
multi-objective optimization
0.212015
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
YearPublicationVenuePosition
2015 MUSCLE: automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis
abstract
Abstract 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