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1.

Figure 1. From: iPE-MMR: An integrated approach to accurately assign monoisotopic precursor masses to tandem mass spectrometric data.

(A) Overall data flow chart of iPE-MMR pipeline. (B) An expanded flow chart of the dotted box of Figure 1a.

Hee-Jung Jung, et al. Anal Chem. ;82(20):8510-8518.
2.
Figure 2

Figure 2. From: iPE-MMR: An integrated approach to accurately assign monoisotopic precursor masses to tandem mass spectrometric data.

Improvement in sensitivity and accuracy of peptide identifications by iPE-MMR. (A) Comparison of number of unique peptide identifications from different methods. (B) Comparison of mass measurement accuracy (MMA) distributions of peptide identifications from different methods. (C) Comparison of distributions of peptide-spectral matches from different methods.

Hee-Jung Jung, et al. Anal Chem. ;82(20):8510-8518.
3.
Figure 6

Figure 6. From: iPE-MMR: An integrated approach to accurately assign monoisotopic precursor masses to tandem mass spectrometric data.

(A) Mass extracted chromatogram of a +2 precursor ion. (B) An averaged isotopic distribution of the corresponding precursor ion. ○ denotes the theoretical isotopic distribution of the predicted peptide (R.NMIIVPEMIGSVVGIYN#GK.A, #=deamidation). (C) Peptide identification without consideration of deamidation. (D) Peptide identification with consideration of deamidation.

Hee-Jung Jung, et al. Anal Chem. ;82(20):8510-8518.
4.
Figure 3

Figure 3. From: iPE-MMR: An integrated approach to accurately assign monoisotopic precursor masses to tandem mass spectrometric data.

Examples of improved peptide identifications after iPE-MMR. (A) The annotated spectrum of Extract_MSn generated DTA. The resultant peptide identification was a reverse sequence peptide. (B) The annotated spectrum of the iPE-MMR generated DTA using the same DTA. The precursor mass was replaced by a UMC mass that was ca. 1 Da smaller. (C) The annotated MS/MS spectrum after DeconMSn. (D) The annotated MS/MS spectrum of the same DTA but after iPE-MMR.

Hee-Jung Jung, et al. Anal Chem. ;82(20):8510-8518.
5.
Figure 4

Figure 4. From: iPE-MMR: An integrated approach to accurately assign monoisotopic precursor masses to tandem mass spectrometric data.

(A) Mass extracted chromatogram of +2 state precursor ions. (B) A spectral summed MS spectrum of the +2 charge state. (C) An annotated MS/MS spectrum of the +2 charge state ion using a DTA mass of 2792.4337. (D) An annotated MS/MS spectrum of the +2 charge state ion after correcting the DTA mass by −1.00235 Da. (E) Mass extracted chromatogram of the +3 state precursor ions. (F) A spectral summed MS spectrum of the +3 charge state. (G) An annotated MS/MS spectrum of a +3 charge state ion using DeconMSn generated DTA. ○ denotes theoretical abundances of the corresponding peptide.

Hee-Jung Jung, et al. Anal Chem. ;82(20):8510-8518.
6.
Figure 5

Figure 5. From: iPE-MMR: An integrated approach to accurately assign monoisotopic precursor masses to tandem mass spectrometric data.

Comparison of plots of mass differential (DelM) versus SEQUEST Xcorr for filtered peptide identification from Extract_MSn generated DTAs (A), iPE-MMR generated DTAs (B), and iPE-MMR generated DTAs with consideration of deamidation (C). Static filters used: ΔCn ≥0.1, Xcorr≥1.9 for +1 peptides, Xcorr≥2.2 for +2 peptides, Xcorr≥3.2 for ≥+3 peptides. Comparison of mass measurement accuracy distributions around each unit bin of DelM of Extract_MSn generated DTAs (D), iPE-MMR generated DTAs (E), and iPE-MMR generated DTAs with consideration of deamidation (F). The numbers are the amount of non-redundant peptide identifications within ±10 ppm of DelM = 0, 1, 2. Peptide identifications around other DelM were not considered as they exhibited complete randomness. For clarity, MS/MS data from the 50% salt fraction was used for this figure.

Hee-Jung Jung, et al. Anal Chem. ;82(20):8510-8518.

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