Convolutional neural network architectures for predicting DNA-protein binding.
Journal:
Bioinformatics (Oxford, England)
Published Date:
Jun 15, 2016
Abstract
MOTIVATION: Convolutional neural networks (CNN) have outperformed conventional methods in modeling the sequence specificity of DNA-protein binding. Yet inappropriate CNN architectures can yield poorer performance than simpler models. Thus an in-depth understanding of how to match CNN architecture to a given task is needed to fully harness the power of CNNs for computational biology applications.