'Ms ms spectra' presentation slideshows

Proteomics: A Challenge for Technology and Information Science

Proteomics: A Challenge for Technology and Information Science. CBCB Seminar, November 21, 2005 Tim Griffin Dept. Biochemistry, Molecular Biology and Biophysics tgriffin@umn.edu. What is proteomics?.

223 views • 22 slides

Protein Identification from Tandem Mass Spectra with Probabilistic Language Modeling

Protein Identification from Tandem Mass Spectra with Probabilistic Language Modeling. Yiming Yang 1,2 , Abhay Harpale 1 and Subramanian Ganaphathy 1 1: Language Technologies Institute 2: Machine Learning Department School of Computer Science, Carnegie Mellon University. Outline.

216 views • 20 slides

LC/MS/MS ??????????????

LC/MS/MS ??????????????. ??????????? ??? ??? ????????? ?? ????? ?. ????. ???????????????????????? ?????????????????????????? ????????????????????????? ????????????????????????

260 views • 15 slides

Bottom-Up Proteomics Data collection

149 views • 14 slides

y 3 -H 3 PO 4

Figure S1 additional MS/MS Spectra and b, y ion tables of Phosphorylated Peptides in KO and WT samples, whose Debunker or A score is lower than the cut-off value . ( ? Indicate to phosphorylated residue). SSWWMLNPEGGKSGK S ? PR. 7. [M+2H] 2+ m/z: 1042.98. MH-H 3 PO 4 2+. y 11.

156 views • 4 slides

MS/MS spectra of NARR phosphopeptides

MS/MS spectra of NARR phosphopeptides.

120 views • 3 slides

2 DGE

MALDI TOF-TOF. Digest Complex Protein Mixture. Protein Spot In-gel Digestion. MDLC. 2 DGE. MS/MS Spectra. Allow for PTM. In-House MASCOT Search ( Macaca Mulatta ). Protein ID. No PTM. Deconvolute. No PTM. De novo Sequence. PEAKS De novo. No Protein ID. Allow for PTM.

171 views • 1 slides

Spectral matching identifies peptides by comparing spectra with libraries of identified spectra

D1. D2. D3. D4. I0. I1. I2. I4. I3. Begin. b1. y1. b2. y2. End. HMMatch : Peptide Identification by Spectral Matching of Tandem Mass Spectra Using Hidden Markov Models. US HUPO.

168 views • 1 slides

The TPP is constantly improved with new functionality.

1.0. sensitivity. 0.8. 0.6. percentage. 0.6. 0.2. error rate. 0. 0.2. 0.4. 0.6. 0.8. 0. 1.0. minimum probability threshold. model results. incorrect. correct. raw MS/MS data file. New Developments for Open-Source Shotgun Proteomics Analysis with the Trans-Proteomic Pipeline

67 views • 1 slides