Finally, based on Bayesian inference, we present a few advanced methods particularly designed for some mass spectrometry data processing problems.
Liquid chromatography-based mass spectrometry has common problems with reproducibility due to technical limitations [21].
Ionization suppression in mass spectrometry is a significant problem that needs to be overcome for mass spectrometry to be used as a detector in proteome analysis.
The mass spectrometry data exist shifting problem which make the m/z scale not stationary.
At the 2014 Fields-MPrime Industrial Problem Solving Workshop, PerkinElmer presented a design problem for mass spectrometry.
To address this problem, multidimensional mass spectrometry (MS) techniques have been evaluated for the separation and identification of polymeric macrocycles.
Now, a technique called tandem mass spectrometry has cleared up the problem.
Most importantly, we presented a new problem in mass spectrometry and provide a baseline method for analysis.
As with mass spectrometry data, there remains the problem that the same peaks across electropherograms are not perfectly aligned in general [ 34, 35].
Because of the undersampling problem of mass spectrometry (MS), the pooled labeled glycopeptides from each digestion strategy were analyzed by 2D nanoLC-MS/MS three times (three replicate runs) to achieve as much information as possible for the sample.
