DICP OpenIR
Subject Area物理化学
Data mining algorithms to improve the sensitivity and reliability for protein and protein phosphorylation identification in shotgun proteomics
Jiang XN(江新宁); Ye ML(叶明亮); Han GH(韩广辉); Zou HF(邹汉法)
Conference NameThe 24th International Symposium on Micro-scale Bioseparation,
Conference Date2009-10-19
2009-10-19
Conference Place中国
Pages76/1
Department十八室
Funding Organization大连化物所
AbstractIn order to overcome the high rick resulting from the model based algorithm while processing dataset with very different characteristics, data mining algorithms were developed to improve the sensitivity for peptide and protein identifications safely. A filtering criteria optimization strategy using genetic algorithm was developed for the determination of tailored filtering criteria for different datasets; and an instance based algorithm using local false discovery rate (local FDR) was developed for the estimation of peptide identification posterior probability by incorporating of k nearest neighbors algorithm and Shannon information entropy strategy. By combining phosphopeptide identification information from MS2 and its consecutive MS3 spectra, an automatic phosphopeptide identification algorithm was developed to overcome the difficulties for phosphopeptide identifications, high FDR and the fact that manual validation is highly relied for the generation of high confident phosphopeptide identifications. By using this strategy, high confidence and sensitivity were achieved for phosphopeptide identification and phosphorylation site localization without the need of manual validation even for low accuracy mass spectrometry. Then a software suite targeted for the validating and processing of phosphoproteome dataset was established to help researchers to generate high confident phosphopeptide/phosphoprotein identifications and prepare phosphoproteome dataset with sufficient information easily. Keywords: Shotgun proteomics/ data mining/ bioinformatics/ phosphorylation/ References 1. Jiang, X. N., Jiang, X. G., Han, G. H., Ye, M. L. and Zou, H. F. Optimization of filtering criterion for SEQUEST database searching to improve proteome coverage in shotgun proteomics BMC Bioinformatics 2007, 8:323. 2. Jiang, X. N., Han, G. H., Feng, S., Jiang, X. G., Ye, M. L., Yao, X. B. and Zou, H. F. Automatic Validation of Phosphopeptide Identifications by the MS2/MS3 Target-Decoy Search Strategy J. Proteome Res. 2008, 7, 1640-1649. 3. Jiang, X. N., Dong, X. L., Ye, M. L. and Zou, H. F. Instance Based Algorithm for Posterior Probability Calculation by Target-Decoy Strategy to Improve Protein Identifications Anal. Chem. 2008, 80, 9326-9335.
Language中文
Document Type会议论文
Identifierhttp://cas-ir.dicp.ac.cn/handle/321008/113824
Collection中国科学院大连化学物理研究所
Corresponding AuthorZou HF(邹汉法)
Recommended Citation
GB/T 7714
Jiang XN,Ye ML,Han GH,et al. Data mining algorithms to improve the sensitivity and reliability for protein and protein phosphorylation identification in shotgun proteomics[C],2009:76/1.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[江新宁]'s Articles
[叶明亮]'s Articles
[韩广辉]'s Articles
Baidu academic
Similar articles in Baidu academic
[江新宁]'s Articles
[叶明亮]'s Articles
[韩广辉]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[江新宁]'s Articles
[叶明亮]'s Articles
[韩广辉]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.