Martin Preusse, Gökcen Eraslan - Deep modeling of DNA sequences with Python & Keras

Ordered sequences of molecules are the central concept of biological
information. The DNA is composed of the 4 nucleotides (A, C, G, T) and is used to persist information over generations. Our understanding of these DNA sequences is very limited. We cannot read them like a book, we still have not learned their grammar and vocabulary. Consequently, there is no way to predict the biological purpose of a stretch of DNA from the sequence alone.

Deep learning methods offer new ways to bring light into the darkness of our genome and to elucidate the structure of genes and their regulation. In this talk, we give an overview of biological sequences, and we demonstrate convolutional neural networks and their applications to classification of DNA sequences. Finally, an implementation of the described neural network written in Keras is presented.