• RNA-Protein Binding Sites Prediction via Multi Scale Convolutional Gated Recurrent Unit Networks

    13 days ago - By IEEE/ACM

    RNA-Protein binding plays important roles in the field of gene expression. With the development of high throughput sequencing, several conventional methods and deep learning-based methods have been proposed to predict the binding preference of RNA-protein binding. These methods can hardly meet the need of consideration of the dependencies between subsequence and the various motif lengths of different translation factors. To overcome such limitations, we propose a predictive model that utilizes a combination of multi-scale convolutional layers and bidirectional gated recurrent unit layer...
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  • Predicting DNA Methylation States with Hybrid Information Based Deep-Learning Model

    13 days ago - By IEEE/ACM

    DNA methylation plays an important role in the regulation of some biological processes. Up to now, with the development of machine learning models, there are several sequence-based deep learning models designed to predict DNA methylation states, which gain better performance than traditional methods like random forest and SVM. However, convolutional network based deep learning models that use one-hot encoding DNA sequence as input may discover limited information and cause unsatisfactory prediction performance, so more data and model structures of diverse angles should be considered. In...
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