ANN Model for Predicting Protein Localization Sites in Cells

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Abstract
To automate examination of massive amounts of sequence data for biological function, it is important to computerize interpretation based on empirical knowledge of sequence-function relationships. For this purpose, we have been constructing an Artificial Neural Network (ANN) by organizing various experimental and computational observations as a collection ANN models. Here we propose an ANN model which utilizes the Dataset for UCI Machine Learning Repository, for predicting localization sites of proteins. We collected data for 336 proteins with known localization sites and divided them into training data and validating data. It was found that the accuracy rate for predicting Protein Localization Sites in Cells is 92.11%. This Indicates that Artificial Neural Network approach is powerful and flexible enough to be used in Protein Localization Sites prediction.
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Archival date: 2020-09-28
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2020-09-28

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