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. Author manuscript; available in PMC: 2014 Nov 1.
Published in final edited form as: J Am Soc Mass Spectrom. 2013 May 16;24(11):1623–1633. doi: 10.1007/s13361-013-0621-1

Figure 3. Construction of decision tree laser power settings.

Figure 3

Precursors of varying charge state were interrogated by AI-ETD with laser powers at 30, 40, and 50 W. The probability of identification for 50 m/z bins for +3 precursors demonstrates the need for higher laser powers at higher m/z (A). Analysis identical to (A) was performed for charge states 2, 3, 4, 5, and >5 and plots were used to construct decision tree logic for AI-ETD laser power settings depending on precursor z and m/z (B). Here, the laser power setting that produced the highest probability of PSM was chosen as the value in the decision tree.