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Mitochondrial proteins remain the subject of intense research interest due to their implication in an increasing number of different conditions including mitochondrial and metabolic disease, cancer, and neuromuscular degenerative and age-related disorders. However, the mitochondrial proteome has yet to be accurately and comprehensively defined, despite many studies. To support mitochondrial research, we developed MitoMiner (http://mitominer.mrc-mbu.cam.ac.uk), a freely accessible mitochondrial proteomics database. MitoMiner integrates different types of subcellular localisation evidence with protein information from public resources, and so provides a comprehensive central resource for data on mitochondrial protein localisation. Here we report important updates to the database including the addition of subcellular immunofluorescent staining results from the Human Protein Atlas, computational predictions of mitochondrial targeting sequences, and additional large-scale mass-spectrometry and GFP tagging data sets. This evidence is shared across the 12 species in MitoMiner (now including Schizosaccharomyces pombe) by homology mapping. MitoMiner provides multiple ways of querying the data including simple text searches, predefined queries and custom queries created using the interactive QueryBuilder. For remote programmatic access, API's are available for several programming languages. This combination of data and flexible querying makes MitoMiner a unique platform to investigate mitochondrial proteins, with application in mitochondrial research and prioritising candidate mitochondrial disease genes. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

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.