69 citations · 84 across the 2 of their papers we have counts for
4 papers
Learning to Plan Chemical Syntheses
Marwin H. S. Segler, Mike Preuss, Mark P. Waller
From medicines to materials, small organic molecules are indispensable for human well-being. To plan their syntheses, chemists employ a problem solving technique called retrosynthe…
Towards "AlphaChem": Chemical Synthesis Planning with Tree Search and Deep Neural Network Policies
Marwin Segler, Mike Preuß, Mark P. Waller
Retrosynthesis is a technique to plan the chemical synthesis of organic molecules, for example drugs, agro- and fine chemicals. In retrosynthesis, a search tree is built by analysi…
Generating Focussed Molecule Libraries for Drug Discovery with Recurrent Neural Networks
Marwin H. S. Segler, Thierry Kogej, Christian Tyrchan +1
In de novo drug design, computational strategies are used to generate novel molecules with good affinity to the desired biological target. In this work, we show that recurrent neur…
Modelling Chemical Reasoning to Predict Reactions
Marwin H. S. Segler, Mark P. Waller
The ability to reason beyond established knowledge allows Organic Chemists to solve synthetic problems and to invent novel transformations. Here, we propose a model which mimics ch…