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

نویسندگان

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

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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عنوان ژورنال:

دوره 31  شماره 

صفحات  -

تاریخ انتشار 2015