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Figure 2 | BMC Bioinformatics

Figure 2

From: A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data

Figure 2

Verification of the features that potentially influence peptide fragmentation. The importance of the features listed in Table 1 is evaluated by the Bayesian neural network and the results are shown: Red circles: normalized irrelevance scores of the features under non-mobile status. Blue squares: normalized irrelevance scores of the features under partial-mobile status. Green triangles: normalized irrelevance scores of the features under mobile status. The higher an irrelevance score is, the less important the corresponding feature is. The threshold of each mobility status is shown in dashed line and the features proven to be influential on peptides' fragmentation (below threshold) are highlighted with filled circles/squares/triangles.

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