MUSCLE : automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis: Automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis

James Bradbury; Grégory Genta-Jouve; James Allwood; Warwick B. Dunn; Royston Goodacre; Joshua D. Knowles; Shan He; Mark R. Viant

doi:10.1093/bioinformatics/btu740

MUSCLE : automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis: Automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis

James Bradbury, Grégory Genta-Jouve, James Allwood, Warwick B. Dunn, Royston Goodacre, Joshua D. Knowles, Shan He, Mark R. Viant^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

8 Citations (Scopus)

169 Downloads (Pure)

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.

Original language	English
Pages (from-to)	975-977
Number of pages	3
Journal	Bioinformatics
Volume	31
Issue number	6
Early online date	11 Nov 2014
DOIs	https://doi.org/10.1093/bioinformatics/btu740
Publication status	Published - 2015

ASJC Scopus subject areas

Biochemistry
Molecular Biology
Computational Theory and Mathematics
Computer Science Applications
Computational Mathematics
Statistics and Probability

Access to Document

10.1093/bioinformatics/btu740Licence: Creative Commons: Attribution (CC BY)

Bradbury_et_al_MUSCLE_automated_multi_objective_Bioinformatics_2015
Eligibility for repository : checked 25/02/2015
Final published version, 127 KBLicence: Creative Commons: Attribution (CC BY)

MUSCLE: Multi-platform Unbiased-optimisation of Spectrometry via Closed Loop Experimentation
Viant, M. (Principal Investigator), He, S. (Co-Investigator) & Cooper, H. (Co-Investigator)
Biotechnology & Biological Sciences Research Council
23/04/12 → 22/06/13
Project: Research Councils

Cite this

Bradbury, J., Genta-Jouve, G., Allwood, J., Dunn, W. B., Goodacre, R., Knowles, J. D., He, S., & Viant, M. R. (2015). MUSCLE : automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis: Automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis. Bioinformatics, 31(6), 975-977. https://doi.org/10.1093/bioinformatics/btu740

@article{af9d088e4809436a8fe679c5ad461c15,

title = "MUSCLE : automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis: Automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis",

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{\textquoteright}s LC-MS/MS instruments.",

author = "James Bradbury and Gr{\'e}gory Genta-Jouve and James Allwood and Dunn, {Warwick B.} and Royston Goodacre and Knowles, {Joshua D.} and Shan He and Viant, {Mark R.}",

year = "2015",

doi = "10.1093/bioinformatics/btu740",

language = "English",

volume = "31",

pages = "975--977",

journal = "Bioinformatics",

issn = "1367-4803",

publisher = "Oxford University Press",

number = "6",

}

TY - JOUR

T1 - MUSCLE : automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis

T2 - Automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis

AU - Bradbury, James

AU - Genta-Jouve, Grégory

AU - Allwood, James

AU - Dunn, Warwick B.

AU - Goodacre, Royston

AU - Knowles, Joshua D.

AU - He, Shan

AU - Viant, Mark R.

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84925240177&partnerID=8YFLogxK

U2 - 10.1093/bioinformatics/btu740

DO - 10.1093/bioinformatics/btu740

M3 - Article

C2 - 25388146

SN - 1367-4803

VL - 31

SP - 975

EP - 977

JO - Bioinformatics

JF - Bioinformatics

IS - 6

ER -

MUSCLE : automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis: Automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis

Abstract

ASJC Scopus subject areas

Access to Document

Fingerprint

Projects

MUSCLE: Multi-platform Unbiased-optimisation of Spectrometry via Closed Loop Experimentation

Cite this