期刊
JOURNAL OF PROTEOME RESEARCH
卷 13, 期 1, 页码 107-113出版社
AMER CHEMICAL SOC
DOI: 10.1021/pr400884c
关键词
protein expression; proteomics; multiomics; metadata; database; protein concentration; data integration
资金
- National Science Foundation under the Division of Biological Infrastructure [0969929]
- National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health [U01DK089571, U01DK072473]
- Seattle Children's Research Institute
- Robert B. McMillen Foundation
- Gordon and Betty Moore Foundation
- Direct For Biological Sciences
- Div Of Biological Infrastructure [0969929] Funding Source: National Science Foundation
The Model Organism Protein Expression Database (MOPED, http://moped.proteinspire.org) is an expanding proteomics resource to enable biological and biomedical discoveries. MOPED aggregates simple, standardized and consistently processed summaries of protein expression and metadata from proteomics (mass spectrometry) experiments from human and model organisms (mouse, worm, and yeast). The latest version of MOPED adds new estimates of protein abundance and concentration as well as relative (differential) expression data. MOPED provides a new updated query interface that allows users to explore information by organism, tissue, localization, condition, experiment, or keyword. MOPED supports the Human Proteome Project's efforts to generate chromosome- and diseases-specific proteomes by providing links from proteins to chromosome and disease information as well as many complementary resources. MOPED supports a new omics metadata checklist to harmonize data integration, analysis, and use. MOPED's development is driven by the user community, which spans 90 countries and guides future development that will transform MOPED into a multiomics resource. MOPED encourages users to submit data in a simple format: They can use the metadata checklist to generate a data publication for this submission. As a result, MOPED will provide even greater insights into complex biological processes, and systems and enable deeper and more comprehensive biological and biomedical discoveries.
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