Prediction of protein subcellular locations using Markov chain models

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Prediction of protein subcellular locations using Markov chain models.

A novel method was introduced to predict protein subcellular locations from sequences. Using sequence data, this method achieved a prediction accuracy higher than previous methods based on the amino acid composition. For three subcellular locations in a prokaryotic organism, the overall prediction accuracy reached 89.1%. For eukaryotic proteins, prediction accuracies of 73.0% and 78.7% were att...

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Prediction of protein subcellular locations using fuzzy k-NN method

MOTIVATION Protein localization data are a valuable information resource helpful in elucidating protein functions. It is highly desirable to predict a protein's subcellular locations automatically from its sequence. RESULTS In this paper, fuzzy k-nearest neighbors (k-NN) algorithm has been introduced to predict proteins' subcellular locations from their dipeptide composition. The prediction i...

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The lethality of a gene is a fundamental and representative measure for understanding the function of a gene and its associated bio-systems. Recently, many research groups have started focusing on the concept of synthetic lethality. The synthetic lethality between genes is defined by the combination of mutations in two genes causing cell death. Here, we confirm that synthetic lethality and cell...

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ژورنال

عنوان ژورنال: FEBS Letters

سال: 1999

ISSN: 0014-5793

DOI: 10.1016/s0014-5793(99)00506-2