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This Article Free via Author's Choice: AC AC Full Text Full Text (PDF) AC All Versions of this Article: M800373-MCP200v1 8/6/1324    most recent Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Glossary Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Smith, A. C. Articles by Robinson, A. J. Search for Related Content PubMed PubMed Citation Articles by Smith, A. C. Articles by Robinson, A. J. Social Bookmarking                      What's this?

Molecular & Cellular Proteomics 8:1324-1337, 2009.
© 2009 by The American Society for Biochemistry and Molecular Biology, Inc.

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Research

MitoMiner, an Integrated Database for the Storage and Analysis of Mitochondrial Proteomics Data^*

Anthony C. Smith and Alan J. Robinson

From the MRC Mitochondrial Biology Unit, Hills Road, Cambridge CB2 0XY, United Kingdom

Mitochondria are a vital component of eukaryotic cells with functions that extend beyond energy production to include metabolism, signaling, cell growth, and apoptosis. Their dysfunction is implicated in a large number of metabolic, degenerative, and age-related human diseases. Therefore, it is important to characterize and understand the mitochondrion. Many experiments have attempted to define the mitochondrial proteome, resulting in large and complex data sets that are difficult to analyze. To address this, we developed a new public resource for the storage and investigation of this mitochondrial proteomics data, called MitoMiner, that uses a model to describe the proteomics data and associated biological information. The proteomics data of 33 publications from both mass spectrometry and green fluorescent protein tagging experiments were imported and integrated with protein annotation from UniProt and genome projects, metabolic pathway data from Kyoto Encyclopedia of Genes and Genomes, homology relationships from HomoloGene, and disease information from Online Mendelian Inheritance in Man. We demonstrate the strengths of MitoMiner by investigating these data sets and show that the number of different mitochondrial proteins that have been reported is about 3700, although the number of proteins common to both animals and yeast is about 1400, and membrane proteins appear to be underrepresented. Furthermore analysis indicated that enzymes of some cytosolic metabolic pathways are regularly detected in mitochondrial proteomics experiments, suggesting that they are associated with the outside of the outer mitochondrial membrane. The data and advanced capabilities of MitoMiner provide a framework for further mitochondrial analysis and future systems level modeling of mitochondrial physiology.

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