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Literature DB >> 16896060

Challenges and opportunities in proteomics data analysis.

Abstract

Accurate, consistent, and transparent data processing and analysis are integral and critical parts of proteomics workflows in general and for biomarker discovery in particular. Definition of common standards for data representation and analysis and the creation of data repositories are essential to compare, exchange, and share data within the community. Current issues in data processing, analysis, and validation are discussed together with opportunities for improving the process in the future and for defining alternative workflows.

Mesh：

Substances：
Peptides
Proteins

Year: 2006 PMID： 16896060 DOI： 10.1074/mcp.R600012-MCP200

Source DB: PubMed Journal: Mol Cell Proteomics ISSN： 1535-9476 Impact factor: 5.911

Keyword Cloud
Cited

33 in total

1. Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring.

Authors: Vinzenz Lange; Johan A Malmström; John Didion; Nichole L King; Björn P Johansson; Juliane Schäfer; Jonathan Rameseder; Chee-Hong Wong; Eric W Deutsch; Mi-Youn Brusniak; Peter Bühlmann; Lars Björck; Bruno Domon; Ruedi Aebersold
Journal: Mol Cell Proteomics Date: 2008-04-13 Impact factor: 5.911

2. Bayesian nonparametric model for the validation of peptide identification in shotgun proteomics.

Authors: Jiyang Zhang; Jie Ma; Lei Dou; Songfeng Wu; Xiaohong Qian; Hongwei Xie; Yunping Zhu; Fuchu He
Journal: Mol Cell Proteomics Date: 2008-11-12 Impact factor: 5.911

3. Building consensus spectral libraries for peptide identification in proteomics.

Authors: Henry Lam; Eric W Deutsch; James S Eddes; Jimmy K Eng; Stephen E Stein; Ruedi Aebersold
Journal: Nat Methods Date: 2008-09-21 Impact factor: 28.547

4. Identification of five candidate lung cancer biomarkers by proteomics analysis of conditioned media of four lung cancer cell lines.

Authors: Chris Planque; Vathany Kulasingam; Chris R Smith; Karen Reckamp; Lee Goodglick; Eleftherios P Diamandis
Journal: Mol Cell Proteomics Date: 2009-09-23 Impact factor: 5.911

Challenges and opportunities in proteomics data analysis.

1. Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring.

2. Bayesian nonparametric model for the validation of peptide identification in shotgun proteomics.

3. Building consensus spectral libraries for peptide identification in proteomics.

4. Identification of five candidate lung cancer biomarkers by proteomics analysis of conditioned media of four lung cancer cell lines.

5. Biomarker discovery in animal health and disease: the application of post-genomic technologies.

6. The FAST-AIMS Clinical Mass Spectrometry Analysis System.

7. Proteomics: challenges, techniques and possibilities to overcome biological sample complexity.

8. Feature detection techniques for preprocessing proteomic data.

9. Identification of glutathione S-transferase pi as a protein involved in Parkinson disease progression.

10. A HUPO test sample study reveals common problems in mass spectrometry-based proteomics.