The main Jupyter notebook practice for building a deep-learning model that classifies whether a DNA sequence would bind an arbitrary transcription factor (TF) based on supplied data, where each DNA sequence is pre-labelled '1' or '0' if the TF does or doesn't bind. The notebook aims to demonstrate the process of loading, processing, and classifying DNA sequences using machine learning techniques.
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DNN for classifying TFs that bind to an ambiguous promoter region
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