Abstract
Compared to other data-intensive disciplines such as genomics, public deposition and storage of MS-based proteomics, data are still less developed due to, among other reasons, the inherent complexity of the data and the variety of data types and experimental workflows. In order to address this need, several public repositories for MS proteomics experiments have been developed, each with different purposes in mind. The most established resources are the Global Proteome Machine Database (GPMDB), PeptideAtlas, and the PRIDE database. Additionally, there are other useful (in many cases recently developed) resources such as ProteomicsDB, Mass Spectrometry Interactive Virtual Environment (MassIVE), Chorus, MaxQB, PeptideAtlas SRM Experiment Library (PASSEL), Model Organism Protein Expression Database (MOPED), and the Human Proteinpedia. In addition, the ProteomeXchange consortium has been recently developed to enable better integration of public repositories and the coordinated sharing of proteomics information, maximizing its benefit to the scientific community. Here, we will review each of the major proteomics resources independently and some tools that enable the integration, mining and reuse of the data. We will also discuss some of the major challenges and current pitfalls in the integration and sharing of the data.
Highlights
The aim of this review is to provide an up-to-date overview of the current state of proteomics data repositories and databases, providing a solid starting point for those who want to perform data submission and/or data mining
Peptide and protein identifications are mapped to a comprehensive reference protein database (for the latest human builds, the searched database is a combination of UniProtKB/Swiss-Prot, Ensembl, and sequences from the International Protein Index (IPI)), and postprocessed using the trans-proteomic pipeline (TPP) [72]
The major differences with other repositories are as follows: (i) it does not exclusively contain MS-derived data, as mentioned already; (ii) data from proteomics experiments are viewed in the context of a protein–protein interaction resource (HPRD); (iii) it restricts the data to that derived from human tissues or cell lines; and (iv) data annotation related to various protein features can be done manually
Summary
Compared to other data-intensive fields such as genomics, deposition and storage of original proteomics, data in public resources have been less common [13]. This is regrettable since proteome studies are usually more complex than its counterpart genomics ones. The audience interested in proteomics data is very heterogeneous It includes, biologists elucidating the mechanisms of regulation of specific proteins, MS researchers improving the current analytical methods, or computational biologists developing new software tools for the analysis and interpretation of the data [24].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
