Convolutional Kitchen Sinks for Transcription Factor Binding Site Prediction

2017-05-31

We present a simple and efficient method for prediction of transcription factor binding sites from DNA sequence. Our method computes a random approximation of a convolutional kernel feature map from DNA sequence and then learns a linear model from the approximated feature map. Our method outperforms state-of-the-art deep learning methods on five out of six test datasets from the ENCODE consortium, while training in less than one eighth the time.

📄 PDF Abstract BibTeX arXiv:1706.00125

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Prediction Transcription Factor Binding Site Prediction

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