Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

James William Allwood

dblp:140/3632 · DBLP profile ↗
← Back
2ranked-venue papers
0as first author
0since 2021 · last 2015
0000-0001-6433-2694ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

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
2 papers
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
metabolomics
0.422015
MUSCLE: automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis · Bioinform. 2015
HAMMER: automated operation of mass frontier to construct in silico mass spectral fragmentation libraries · Bioinform. 2014
Bioinformatics and computational biology
multi-objective optimization
0.212015
MUSCLE: automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis · Bioinform. 2015
Bioinformatics and computational biology › metabolomics
metabolite identification
0.212014
HAMMER: automated operation of mass frontier to construct in silico mass spectral fragmentation libraries · Bioinform. 2014

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.3
2014 HAMMER: automated operation of mass frontier to construct in silico mass spectral fragmentation libraries
abstract
SUMMARY: Experimental MS(n) mass spectral libraries currently do not adequately cover chemical space. This limits the robust annotation of metabolites in metabolomics studies of complex biological samples. In silico fragmentation libraries would improve the identification of compounds from experimental multistage fragmentation data when experimental reference data are unavailable. Here, we present a freely available software package to automatically control Mass Frontier software to construct in silico mass spectral libraries and to perform spectral matching. Based on two case studies, we have demonstrated that high-throughput automation of Mass Frontier allows researchers to generate in silico mass spectral libraries in an automated and high-throughput fashion with little or no human intervention required. AVAILABILITY AND IMPLEMENTATION: Documentation, examples, results and source code are available at http://www.biosciences-labs.bham.ac.uk/viant/hammer/.
Ralf J. M. Weber, James William Allwood, Robert Mistrik, Zexuan Zhu 0001, Zhen Ji, Siping Chen, Warwick B. Dunn, Shan He 0001, Mark R. Viant
Bioinform.3