Employing deep learning to study biomolecules

Abstract

Deep learning and neural networks are at the frontier of machine learning and artificial intelligence. The applications of these methods are vast and include many applications within bioscience. Most recently, Google’s Deep Mind project stunned the protein structure prediction community with their performance in the last critical assessment of structural prediction (CASP) competition. The objective of this tutorial is three-fold. First, the tutorial will introduce students and researchers that attend to the Keras deep learning framework. This library will be paired with Google’s TensorFlow backend and examples will be shown utilizing both the Python and R programming languages. Second, the tutorial will allow attendees to learn the basic concepts of convolutional neural networks, recurrent neural networks, and transfer learning. Hands-on examples and sample code will be provided for each of these separate topics using classic example problems (such as image recognition/classification and text-mining/sentiment analysis). Third, an in class competition to identify antimicrobial peptides will employ multiple concepts collectively. An accompanying web server will allow attendees to upload and evaluate their models on the fly and further see how it ranks and compares to others.