Apr 12, 2018 � Here, we present DeepPolyA, a new deep convolutional neural network-based approach, to predict polyadenylation sites from the plant Arabidopsis�...
Here, we present DeepPolyA, a new deep convolutional neural network-based approach, to predict polyadenylation sites from the plant. Arabidopsis thaliana�...
DeepPolyA, a new deep convolutional neural network-based approach, to predict polyadenylation sites from the plant Arabidopsis thaliana gene sequences is�...
Apr 12, 2018 � Here, we present DeepPolyA, a new deep convolutional neural network-based approach, to predict polyadenylation sites from the plant Arabidopsis�...
Use DeepPolyA convolutional neural network to predict cis regulatory element which may play a role in polyadenylation. Or use the combination of poly(A) signal,�...
In this paper, we propose a new deep learning model, called DeepPASTA, for predicting polyA sites from both sequence and RNA secondary structure data.
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Nov 15, 2023 � The convolutional network of our deep learning models extracts predictive sequence motifs and can be used to generate quantitative measurements�...
Jun 27, 2020 � A deep neural network enables precise engineering of polyadenylation signals, identifies human genetic variants that act through mis-regulating APA,
Nov 5, 2020 � Poly(A)-DG consists of a Convolution Neural Network-Multilayer Perceptron (CNN-MLP) network and a domain generalization technique.
Most methods use convolution neural networks (CNNs), such as DeepPolyA [71], Conv-Net [72], DeeReCT-PolyA [26], DeepPASTA [28], DeepGSR [27], and APARENT [29].