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MUSCLE: automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis.
Bradbury, James; Genta-Jouve, Grégory; Allwood, J William; Dunn, Warwick B; Goodacre, Royston; Knowles, Joshua D; He, Shan; Viant, Mark R.
Afiliación
  • Bradbury J; School of Computer Science and School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK, Manchester Institute of Biotechnology, School of Chemistry and School of Computer Science, The University of Manchester, Manchester M13 9JD, UK.
  • Genta-Jouve G; School of Computer Science and School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK, Manchester Institute of Biotechnology, School of Chemistry and School of Computer Science, The University of Manchester, Manchester M13 9JD, UK.
  • Allwood JW; School of Computer Science and School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK, Manchester Institute of Biotechnology, School of Chemistry and School of Computer Science, The University of Manchester, Manchester M13 9JD, UK.
  • Dunn WB; School of Computer Science and School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK, Manchester Institute of Biotechnology, School of Chemistry and School of Computer Science, The University of Manchester, Manchester M13 9JD, UK.
  • Goodacre R; School of Computer Science and School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK, Manchester Institute of Biotechnology, School of Chemistry and School of Computer Science, The University of Manchester, Manchester M13 9JD, UK School of Computer Science and School of
  • Knowles JD; School of Computer Science and School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK, Manchester Institute of Biotechnology, School of Chemistry and School of Computer Science, The University of Manchester, Manchester M13 9JD, UK.
  • He S; School of Computer Science and School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK, Manchester Institute of Biotechnology, School of Chemistry and School of Computer Science, The University of Manchester, Manchester M13 9JD, UK.
  • Viant MR; School of Computer Science and School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK, Manchester Institute of Biotechnology, School of Chemistry and School of Computer Science, The University of Manchester, Manchester M13 9JD, UK.
Bioinformatics ; 31(6): 975-7, 2015 Mar 15.
Article en En | MEDLINE | ID: mdl-25388146
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Esteroides / Programas Informáticos / Cromatografía Liquida Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2015 Tipo del documento: Article Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Esteroides / Programas Informáticos / Cromatografía Liquida Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2015 Tipo del documento: Article Pais de publicación: Reino Unido