Protein Mass Spectrometry Analysis Databases
Protein mass spectrometry analysis databases are foundational to bioinformatics resources, serving as an indispensable element for proteomics research. By seamlessly integrating proteomics and computational biology, these databases enable the accurate identification and quantification of proteins across diverse biological samples.
Key Roles of Protein Mass Spectrometry Analysis Databases
As repositories for identified protein mass spectrometry data, these databases store not only the mass spectrometry results but also essential metadata, including sample origins, experimental conditions, and analytical tools. This comprehensive information empowers researchers to compare mass spectrometry datasets across different experiments, species, and disease models. Such comparative analyses facilitate the identification of protein expression patterns under specific conditions, the discovery of disease biomarkers, and the exploration of novel drug targets.
Prominent Examples of Protein Mass Spectrometry Analysis Databases
1. PRIDE (Proteomics Identifications Database)
A publicly accessible repository hosted by the European Bioinformatics Institute, PRIDE compiles mass spectrometry data from global contributions, supporting a wide range of proteomics research.
2. PeptideAtlas
Managed by the Institute for Systems Biology in Seattle, PeptideAtlas provides an extensive collection of peptide-level mass spectrometry data, offering a valuable resource for peptide-centric studies.
3. GPM (Global Proteome Machine)
GPM integrates a vast array of protein mass spectrometry datasets and includes an open-source software platform for protein identification and quantification, supporting broad applications in proteomics.
Protein mass spectrometry analysis databases play a pivotal role in advancing proteomics by facilitating the sharing and reuse of experimental data. Their contributions significantly enhance the reproducibility and scalability of proteomics research, driving scientific innovation in protein studies.
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