Sentence examples for mass spectral deconvolution from inspiring English sources

GC-MS spectra were processed as peaks deconvoluted using the Automated Mass Spectral Deconvolution and Identification System (AMDIS, Version 2.64, NIST, US) and subsequently filtered using spectconnect (http://spectconnect.mit.edu/; PMID: 17263323).

The measured mass spectra were deconvoluted by the Automated Mass Spectral Deconvolution and Identification System (AMDIS 2.64, NIST Gaithersburg, MD) before comparison with the databases.

GC-MS spectra were deconvoluted using the Automated Mass Spectral Deconvolution and Identification System (AMDIS version 2.64) and compared with reference spectra in the National Institute of Standards and Technology NISTT version 02) main mass spectral database (match factor ≥70%%) for tentative identification [ 26].

Mass spectra were deconvoluted using the Automated Mass Spectral Deconvolution and Identification System (AMDIS version 2.64) and compared with reference spectra in the National Institute of Standards and Technology NISTT version 02) main mass spectral database (match factor ≥80%) for tentative identification.

The data from GC-MS analysis were deconvoluted in batch mode using the freely available Automated Mass Spectral Deconvolution and Identification System (AMDIS) spectral deconvolution software package (v2.65, NIST Gaithersburg) [ 21].

The automated mass spectral deconvolution and identification system (AMDIS, National Institute of Standards and Technology, Gaithersburg, MD) was first utilized to deconvolute mass peaks and search the self-constructed standard library by matching retention time and mass spectra pattern.

PyMCA was used for batch spectral deconvolution.

User-defined libraries were generated using the automated mass-spectral deconvolution and identification system (AMDIS; National Institute of Standards) to deconvolute GC-MS results and identify distinct chromatographic components.

The web-based MassBank as a community-driven open source approach for peak deconvolution, mass spectral evaluation and library searches, has been established by the metabolomics community[14] and is now adapted to environmental contaminants by the NORMAN EDA WG[15].

A generalised method for the deconvolution of mass spectral data from the aerodyne aerosol mass spectrometer (AMS) is presented.

Finally, while highly sophisticated automation exists for analysis by scanning confocal fluorescence microscopy, robotic hit bead selection, and single-bead hit validation prior to resynthesis, there is sparingly little automation for single-bead chemical cleavage and de novo deconvolution of mass spectral data, severely limiting analysis throughput.