Ultra-deep quantitative proteomics with RT-normalized peptide database
Project/Area Number |
26640092
|
Research Category |
Grant-in-Aid for Challenging Exploratory Research
|
Allocation Type | Multi-year Fund |
Research Field |
Tumor diagnostics
|
Research Institution | Kumamoto University |
Principal Investigator |
Ohtsuki Sumio 熊本大学, 生命科学研究部, 教授 (60323036)
|
Project Period (FY) |
2014-04-01 – 2016-03-31
|
Project Status |
Completed (Fiscal Year 2015)
|
Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2015: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Fiscal Year 2014: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
|
Keywords | プロテオミクス / 質量分析 / 溶出時間 / データベース / プロテオーミクス |
Outline of Final Research Achievements |
The purpose of the present project is to develop deep quantitative proteomics with peptide database by high-accurate retention time normalization and separation of signal to noise. The developed method for retention time normalization and false discovery rate was validated with trypsin-digested human liver microsomes. The developed method was able to eliminate false positives more efficiently and compare lager number of peptide than the standard method. The ability of retention time normalization was evaluated between two institutes, the accuracy of normalization was reduces, however the normalized retention time is possible to be applied to quantitative analysis by changing analysis settings. The developed method was applied to quantitative proteomic analyses for network analysis and biomarker discovery.
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Report
(3 results)
Research Products
(11 results)