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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.
Smith et al. (Thu,) studied this question.