MIA: Wouter Boomsma & Jes Frellsen, Convolutional models of molecular structure

May 23, 2018

MIA Meeting: https://www.youtube.com/watch?v=-UKL3kOlOds&list=PLlMMtlgw6qNjROoMNTBQjAcdx53kV50cS&index=43m15s

Wouter Boomsma and Jes Frellsen
Departments of Computer Science
University of Copenhagen and IT University of Copenhagen

Convolutional models of molecular structure

Abstract: Although originally devised in the field of image analysis, convolutional neural networks (CNNs) are increasingly finding applications outside the image domain. In particular, a number of studies over the last year have made a convincing case for the use of CNNs within the field of molecular modelling. As an example of these recent developments, we will present our work on using convolutions to predict mutation-induced changes-of-stability (ddgs) in proteins. We will demonstrate how a simple convolutional model using a purely data-driven approach achieves performance comparable to that of state-of-the-art methods in the field. Finally, we will discuss current theoretical developments in the area of convolutions, including the quest for rotational equivariance.

Primer: Learning from molecular structure

Abstract: Purely data-driven modelling techniques have had a fundamental impact on the analysis of biological sequences. In particular, neural networks have been used extensively, with successful applications in for instance the prediction of secondary structure, aggregation propensities, and disorder. In contrast, the 3D structure of molecules has been modelled almost exclusively with carefully parameterised physical force fields, which are notoriously difficult to optimise from data. Recent developments in Machine Learning are changing this picture, making it possible to learn structure-sequence relationships directly from raw molecular structures. In this primer, we will briefly review these developments, and introduce the concept of convolutional neural networks, which form the basis for many of the current activities, including the work we will present as our main talk.

For more information on the Broad Institute and MIA visit: http://www.broadinstitute.org/MIA

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