Convolutional neural network architectures for predicting DNA–protein binding
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.
Results: We present a systematic exploration of...
Paper Details
Title
Convolutional neural network architectures for predicting DNA–protein binding
Published Date
Jun 15, 2016
Journal
Volume
32
Issue
12
Pages
121 - 127
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