ngLOC: an n-gram-based Bayesian method for estimating the subcellular proteomes of eukaryotes

ngLOC:一种基于n-gram的贝叶斯方法,用于估计真核生物的亚细胞蛋白质组

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Abstract

We present a method called ngLOC, an n-gram-based Bayesian classifier that predicts the localization of a protein sequence over ten distinct subcellular organelles. A tenfold cross-validation result shows an accuracy of 89% for sequences localized to a single organelle, and 82% for those localized to multiple organelles. An enhanced version of ngLOC was developed to estimate the subcellular proteomes of eight eukaryotic organisms: yeast, nematode, fruitfly, mosquito, zebrafish, chicken, mouse, and human.

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