Interpretable Deep Learning in Drug Discovery

1 code implementation • 7 Mar 2019 • Kristina Preuer, Günter Klambauer, Friedrich Rippmann, Sepp Hochreiter, Thomas Unterthiner

Without any means of interpretation, neural networks that predict molecular properties and bioactivities are merely black boxes.

Drug Discovery

Fréchet ChemNet Distance: A metric for generative models for molecules in drug discovery

2 code implementations • 26 Mar 2018 • Kristina Preuer, Philipp Renz, Thomas Unterthiner, Sepp Hochreiter, Günter Klambauer

We propose a novel distance measure between two sets of molecules, called Fr\'echet ChemNet distance (FCD), that can be used as an evaluation metric for generative models.

Drug Discovery

DeepSynergy: Predicting Anti-Cancer Drug Synergy with Deep Learning

1 code implementation • Bioinformatics 2017 • Kristina Preuer, Richard P I Lewis, Sepp Hochreiter, Andreas Bender, Krishna C Bulusu, Günter Klambauer

While drug combination therapies are a well-established concept in cancer treatment, identifying novel synergistic combinations is challenging due to the size of combinatorial space.