| Chapter title |
Proteomics data exchange and storage: the need for common standards and public repositories.
|
|---|---|
| Chapter number | 14 |
| Book title |
Mass Spectrometry Data Analysis in Proteomics
|
| Published in |
Methods in molecular biology, January 2013
|
| DOI | 10.1007/978-1-62703-392-3_14 |
| Pubmed ID | |
| Book ISBNs |
978-1-62703-391-6, 978-1-62703-392-3
|
| Authors |
Rafael C. Jiménez, Juan Antonio Vizcaíno |
| Abstract |
Both the existence of data standards and public databases or repositories have been key factors behind the development of the existing "omics" approaches. In this book chapter we first review the main existing mass spectrometry (MS)-based proteomics resources: PRIDE, PeptideAtlas, GPMDB, and Tranche. Second, we report on the current status of the different proteomics data standards developed by the Proteomics Standards Initiative (PSI): the formats mzML, mzIdentML, mzQuantML, TraML, and PSI-MI XML are then reviewed. Finally, we present an easy way to query and access MS proteomics data in the PRIDE database, as a representative of the existing repositories, using the workflow management system (WMS) tool Taverna. Two different publicly available workflows are explained and described. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 67% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 4% |
| Unknown | 23 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 33% |
| Student > Bachelor | 4 | 17% |
| Professor > Associate Professor | 3 | 13% |
| Student > Ph. D. Student | 3 | 13% |
| Student > Doctoral Student | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 5 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 29% |
| Agricultural and Biological Sciences | 6 | 25% |
| Computer Science | 3 | 13% |
| Biochemistry, Genetics and Molecular Biology | 2 | 8% |
| Immunology and Microbiology | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 4 | 17% |