Presentation is loading. Please wait.

Presentation is loading. Please wait.

S1R1S1R2S2R1S2R2S1R4 S2R3 S2R4 S1R3 S1R1S1R2S2R1S2R2S1R1S1R2S2R1S2R2 S1R3S1R4S2R3S2R4S1R3S1R4S2R3S2R4 PT SET PT SET PT SET PT SET PT SET PT SET PT SETPT.

Published byHillary Edwards Modified over 8 years ago

Similar presentations

Presentation on theme: "S1R1S1R2S2R1S2R2S1R4 S2R3 S2R4 S1R3 S1R1S1R2S2R1S2R2S1R1S1R2S2R1S2R2 S1R3S1R4S2R3S2R4S1R3S1R4S2R3S2R4 PT SET PT SET PT SET PT SET PT SET PT SET PT SETPT."— Presentation transcript:

1 S1R1S1R2S2R1S2R2S1R4 S2R3 S2R4 S1R3 S1R1S1R2S2R1S2R2S1R1S1R2S2R1S2R2 S1R3S1R4S2R3S2R4S1R3S1R4S2R3S2R4 PT SET PT SET PT SET PT SET PT SET PT SET PT SETPT SET PT- porcine trypsin SET – Streptomyces erythraeus trypsin S1R1S1R2S2R1S2R2S1R1S1R2S2R1S2R2 S1R3S1R4S2R3S2R4S1R3S1R4S2R3S2R4 Protein extraction with B-PER Gel electrophoresis Protein digestion in gel LC-MS/MS analysis – Qstar Elite Database search – Mascot and Xtandem! Protein identification validation and quantitation - Scaffold Optimal biocathodes Suboptimal biocathodes

2 Proteins: 90% protein probability 95% peptide probability At least 1 peptide 579 proteins

3 Peptides: 90% protein probability 95% peptide probability At least 1 peptide

4 Spectra: 90% protein probability 95% peptide probability At least 1 peptide

5 Proteins: 90% protein probability 70% peptide probability At least 2 peptides 286 proteins

6 Peptides: 90% protein probability 70% peptide probability At least 2 peptides

7 Spectra: 90% protein probability 70% peptide probability At least 2 peptides

8 Proteins: 90% protein probability 70% peptide probability At least 2 peptides 286 proteins

9 peptides: 90% protein probability 70% peptide probability At least 2 peptides

10 spectra: 90% protein probability 70% peptide probability At least 2 peptides

11 CategoryBio SampleMS/MS Sample#Prot#IDs#Spec%IDs PTS1R1 PTmascot_daemon_merge (S1R1_gel2_opt_F003330)4320029890.06691201 PTS1R2 PTmascot_daemon_merge (S1R2_gel2_opt_F003339)11067648150.1403946 PTS2R1 PTmascot_daemon_merge (S2R1_gel2_opt_F003342)6426248910.05356778 PTS1R3 PTmascot_daemon_merge (S1R3_gel2_subopt_F003341)5235346160.07647314 PTS1R4 PTmascot_daemon_merge (S1R4_gel2_subopt_F003340)15076062300.12199037 PTS2R3 PTmascot_daemon_merge (S2R3_gel2_subopt_F003343)8541251090.08064201 PTS2R4 PTmascot_daemon_merge (S2R4_gel2_subopt_F003344)4718248570.03747169 PTS2R2 PTmascot_daemon_merge (S2R2_gel2_opt_F003345)6422239330.05644546 SETS1R1 SETmascot_daemon_merge (F003578_S1R1_Oct_9bands)233103334180.30222353 SETS1R3 SETmascot_daemon_merge (F003577_S1R3_Oct_9bands)10637336420.102416255 SETS1R2 SETmascot_daemon_merge (F003582_S1R2_Oct_9bands)19072543130.16809645 SETS1R4 SETmascot_daemon_merge (F003581_S1R4_Oct_9bands)243125070840.17645398 SETS2R1 SETmascot_daemon_merge (F003583_S2R1_Oct_9bands)19054667080.08139535 SETS2R3 SETmascot_daemon_merge (F003584_S2R3_Oct9bands)22575769120.109519675 SETS2R2 SETmascot_daemon_merge (F003586_S2R2_Oct_9bands)20166848120.13881962 SETS2R4 SETmascot_daemon_merge (F003587_S2R4_Oct_9bands)18455947970.11653116

12 Proteins: 90% protein probability 95% peptide probability At least 1 peptide 579 proteins

13 peptides: 90% protein probability 95% peptide probability At least 1 peptide

14 spectra: 90% protein probability 95% peptide probability At least 1 peptide

15 CategoryBio SampleMS/MS Sample#Prot#IDs#Spec%IDs PTS1R1 PTmascot_daemon_merge (S1R1_gel2_opt_F003330)6324329890.08129809 PTS1R2 PTmascot_daemon_merge (S1R2_gel2_opt_F003339)14860248150.12502596 PTS2R1 PTmascot_daemon_merge (S2R1_gel2_optF003342)8727348910.055816807 PTS1R3 PTmascot_daemon_merge (S1R3_gel2_subopt_F003341)7536246160.078422874 PTS1R4 PTmascot_daemon_merge (S1R4_gel2_subopt_F003340)21773862300.11845907 PTS2R3 PTmascot_daemon_merge (S2R3_gel2_subopt_F003343)11142951090.08396947 PTS2R4 PTmascot_daemon_merge (S2R4_gel2_subopt_F003344)7121848570.044883672 PTS2R2 PTmascot_daemon_merge (S2R2_gel2_opt_F003345)8824139330.06127638 SETS1R1 SETmascot_daemon_merge (F003578_S1R1_Oct_9bands)347102834180.3007607 SETS1R3 SETmascot_daemon_merge (F003577_S1R3_Oct_9bands)12137636420.103239976 SETS1R2 SETmascot_daemon_merge (F003582_S1R2_Oct_9bands)24669443130.16090888 SETS1R4 SETmascot_daemon_merge (F003581_S1R4_Oct_9bands)337118070840.16657256 SETS2R1 SETmascot_daemon_merge (F003583_S2R1_Oct_9bands)22648567080.07230173 SETS2R3 SETmascot_daemon_merge (F003584_S2R3_Oct9bands)30872469120.10474537 SETS2R2 SETmascot_daemon_merge (F003586_S2R2_Oct_9bands)27966948120.13902743 SETS2R4 SETmascot_daemon_merge (F003587_S2R4_Oct_9bands)22049347970.10277256

Download ppt "S1R1S1R2S2R1S2R2S1R4 S2R3 S2R4 S1R3 S1R1S1R2S2R1S2R2S1R1S1R2S2R1S2R2 S1R3S1R4S2R3S2R4S1R3S1R4S2R3S2R4 PT SET PT SET PT SET PT SET PT SET PT SET PT SETPT."

Similar presentations

From Genome to Proteome Juang RH (2004) BCbasics Systems Biology, Integrated Biology.

From Genome to Proteome Juang RH (2004) BCbasics Systems Biology, Integrated Biology.
The Proteomics Core at Wayne State University

The Proteomics Core at Wayne State University
ProteinPilot ™ Software © 2008 Applera Corporation and MDS Inc.

ProteinPilot ™ Software © 2008 Applera Corporation and MDS Inc.
UC Mass Spectrometry Facility & Protein Characterization for Proteomics Core Proteomics Capabilities: Examples of Protein ID and Analysis of Modified Proteins.

UC Mass Spectrometry Facility & Protein Characterization for Proteomics Core Proteomics Capabilities: Examples of Protein ID and Analysis of Modified Proteins.
In-depth Analysis of Protein Amino Acid Sequence and PTMs with High-resolution Mass Spectrometry Lian Yang 2 ; Baozhen Shan 1 ; Bin Ma 2 1 Bioinformatics.

In-depth Analysis of Protein Amino Acid Sequence and PTMs with High-resolution Mass Spectrometry Lian Yang 2 ; Baozhen Shan 1 ; Bin Ma 2 1 Bioinformatics.
1336 SW Bertha Blvd, Portland OR 97219

1336 SW Bertha Blvd, Portland OR 97219
N-Glycopeptide Identification from CID Tandem Mass Spectra using Glycan Databases and False Discovery Rate Estimation Kevin B. Chandler, Petr Pompach,

N-Glycopeptide Identification from CID Tandem Mass Spectra using Glycan Databases and False Discovery Rate Estimation Kevin B. Chandler, Petr Pompach,
Biomolecule analysis using Mass Spectrometry. ELECTROPHORESIS / ISOELECTRIC FOCUSING Ettan IPGphor I/II IEF (GE Amersham) Dalt II Separation Unit (GE.

Biomolecule analysis using Mass Spectrometry. ELECTROPHORESIS / ISOELECTRIC FOCUSING Ettan IPGphor I/II IEF (GE Amersham) Dalt II Separation Unit (GE.
Database Searches. Peptide mass fingerprinting digestMS Search HIT SCORE Protein X 1000 Protein Y 50 Protein Z 5 Protein X theoretical digestProtein Y.

Database Searches. Peptide mass fingerprinting digestMS Search HIT SCORE Protein X 1000 Protein Y 50 Protein Z 5 Protein X theoretical digestProtein Y.
Mass Fingerprint. Protease A protease is any enzyme that conducts proteolysis, that is, begins protein catabolism by hydrolysis of the peptide bonds that.

Mass Fingerprint. Protease A protease is any enzyme that conducts proteolysis, that is, begins protein catabolism by hydrolysis of the peptide bonds that.
De Novo Sequencing v.s. Database Search Bin Ma School of Computer Science University of Waterloo Ontario, Canada.

De Novo Sequencing v.s. Database Search Bin Ma School of Computer Science University of Waterloo Ontario, Canada.
Yoona Kim University of California, San Diego UCSD Mass Spectrometry Journal Club 12/03/10.

Yoona Kim University of California, San Diego UCSD Mass Spectrometry Journal Club 12/03/10.
Protein Identification and Peptide Sequencing by Liquid Chromatography – Mass Spectrometry Detlef Schumann, PhD Director, Proteomics Laboratory Department.

Protein Identification and Peptide Sequencing by Liquid Chromatography – Mass Spectrometry Detlef Schumann, PhD Director, Proteomics Laboratory Department.
Protein Identification with Mascot Software (Laxmana Rao Y. and Gopalacharyulu P.V.)

Protein Identification with Mascot Software (Laxmana Rao Y. and Gopalacharyulu P.V.)
Proteomics Informatics – Protein identification II: search engines and protein sequence databases (Week 5)

Proteomics Informatics – Protein identification II: search engines and protein sequence databases (Week 5)
Announcements: Proposal resubmissions are due 4/23. It is recommended that students set up a meeting to discuss modifications for the final step of the.

Announcements: Proposal resubmissions are due 4/23. It is recommended that students set up a meeting to discuss modifications for the final step of the.
Facts and Fallacies about de Novo Sequencing & Database Search.

Facts and Fallacies about de Novo Sequencing & Database Search.
Tryptic digestion Proteomics Workflow for Gel-based and LC-coupled Mass Spectrometry Protein or peptide pre-fractionation is a prerequisite for the reduction.

Tryptic digestion Proteomics Workflow for Gel-based and LC-coupled Mass Spectrometry Protein or peptide pre-fractionation is a prerequisite for the reduction.
Identification of regulatory proteins from human cells using 2D-GE and LC-MS/MS Victor Paromov Christian Muenyi William L. Stone.

Identification of regulatory proteins from human cells using 2D-GE and LC-MS/MS Victor Paromov Christian Muenyi William L. Stone.
1 Quantitative Proteomic Sample Set Amounts displayed as fmols per µg of digested yeast lysate Each sample theoretically contains 15 µg of digested yeast.

1 Quantitative Proteomic Sample Set Amounts displayed as fmols per µg of digested yeast lysate Each sample theoretically contains 15 µg of digested yeast.

Similar presentations

Ads by Google