Use of statistical methods for estimation of total number of charges in a mass spectrometry experiment. Kaur, P. and O'Connor, P. B. Anal Chem, 76(10):2756–2762, 2004.
doi  abstract   bibtex   
Estimation of the number of ions in a mass spectrometry experiment is needed to determine instrumentation parameters such as ionization efficiency, collision-induced dissociation efficiency, ion-transfer efficiency, ion trapping efficiency, and preamplifier detection limit. This work aims at analyzing the statistical characteristics (primarily variance) in the intensities of the isotopic distributions, which depend on the number of ions in the cell. A mathematical derivation was developed based on the maximum likelihood estimation method, which estimates the most likely number of ions in the cell using a method known as nonrandom parameter estimation. The performance of the method improves with increase in the number of observed distributions. The method works well provided the spectra show isotopic resolution and is independent of the instrument or method used to arrive at the spectra.
@Article{kaur04use,
  author    = {Parminder Kaur and Peter B. O'Connor},
  title     = {Use of statistical methods for estimation of total number of charges in a mass spectrometry experiment},
  journal   = {Anal Chem},
  year      = {2004},
  volume    = {76},
  number    = {10},
  pages     = {2756--2762},
  abstract  = {Estimation of the number of ions in a mass spectrometry experiment is needed to determine instrumentation parameters such as ionization efficiency, collision-induced dissociation efficiency, ion-transfer efficiency, ion trapping efficiency, and preamplifier detection limit. This work aims at analyzing the statistical characteristics (primarily variance) in the intensities of the isotopic distributions, which depend on the number of ions in the cell. A mathematical derivation was developed based on the maximum likelihood estimation method, which estimates the most likely number of ions in the cell using a method known as nonrandom parameter estimation. The performance of the method improves with increase in the number of observed distributions. The method works well provided the spectra show isotopic resolution and is independent of the instrument or method used to arrive at the spectra.},
  doi       = {10.1021/ac035334w},
  file      = {Kaur_UseStatisticalMethods_AanlChem_2004.pdf:2004/Kaur_UseStatisticalMethods_AanlChem_2004.pdf:PDF},
  keywords  = {Carbon Isotopes; Data Interpretation, Statistical; Ions; Isotopes; Mass Spectrometry; Myoglobin, chemistry},
  owner     = {kerstin},
  pmid      = {15144185},
  timestamp = {2012.03.13},
}
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