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• W1550117682 abstract "Knowing the submitochondria localization of a mitochondria protein is an important step to understand its function. We develop a method which is based on an extended version of pseudo-amino acid composition to predict the protein localization within mitochondria. This work goes one step further than predicting protein subcellular location. We also try to predict the membrane protein type for mitochondrial inner membrane proteins.By using leave-one-out cross validation, the prediction accuracy is 85.5% for inner membrane, 94.5% for matrix and 51.2% for outer membrane. The overall prediction accuracy for submitochondria location prediction is 85.2%. For proteins predicted to localize at inner membrane, the accuracy is 94.6% for membrane protein type prediction.Our method is an effective method for predicting protein submitochondria location. But even with our method or the methods at subcellular level, the prediction of protein submitochondria location is still a challenging problem. The online service SubMito is now available at: http://bioinfo.au.tsinghua.edu.cn/subMito." @default.
• W1550117682 created "2016-06-24" @default.
• W1550117682 creator A5011271652 @default.
• W1550117682 creator A5033512723 @default.
• W1550117682 date "2006-11-30" @default.
• W1550117682 modified "2023-10-16" @default.
• W1550117682 title "Prediction of protein submitochondria locations by hybridizing pseudo-amino acid composition with various physicochemical features of segmented sequence" @default.
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• W1550117682 doi "https://doi.org/10.1186/1471-2105-7-518" @default.
• W1550117682 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/1716183" @default.
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• W1550117682 hasPublicationYear "2006" @default.
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