Abstract:Nowadays, with the increasing number of protein sequences all over the world, more and more people are paying their attention to predicting protein subcellular location. Since wet experiment is costly and time-consuming, the automatic computational methods are urgent. In this paper, we propose a variant model based on Long Short-Term Memory (LSTM) to predict protein subcellular location. In this model, we employ LSTM to capture long distance dependency features of the sequence data. Moreover, we adjust the los… Show more
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