1 code implementation • 30 Oct 2023 • Krzysztof Maziarz, Austin Tripp, Guoqing Liu, Megan Stanley, Shufang Xie, Piotr Gaiński, Philipp Seidl, Marwin Segler
The planning of how to synthesize molecules, also known as retrosynthesis, has been a growing focus of the machine learning and chemistry communities in recent years.
no code implementations • 13 Oct 2023 • Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Marwin Segler, José Miguel Hernández-Lobato
Retrosynthesis is the task of proposing a series of chemical reactions to create a desired molecule from simpler, buyable molecules.
no code implementations • 30 Aug 2023 • Ilia Igashov, Arne Schneuing, Marwin Segler, Michael Bronstein, Bruno Correia
Retrosynthesis planning is a fundamental challenge in chemistry which aims at designing reaction pathways from commercially available starting materials to a target molecule.
no code implementations • 4 May 2023 • Hagen Muenkler, Hubert Misztela, Michal Pikusa, Marwin Segler, Nadine Schneider, Krzysztof Maziarz
Many contemporary generative models of molecules are variational auto-encoders of molecular graphs.
1 code implementation • 31 Jan 2023 • Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu
Retrosynthesis, which aims to find a route to synthesize a target molecule from commercially available starting materials, is a critical task in drug discovery and materials design.
Ranked #1 on Multi-step retrosynthesis on USPTO-190
1 code implementation • Journal of Chemical Information and Modeling 2022 • Philipp Seidl, Philipp Renz, Natalia Dyubankova, Paulo Neves, Jonas Verhoeven, Jörg K. Wegner, Marwin Segler, Sepp Hochreiter, and Günter Klambauer
Finding synthesis routes for molecules of interest is essential in the discovery of new drugs and materials.
Ranked #11 on Single-step retrosynthesis on USPTO-50k
1 code implementation • 7 Apr 2021 • Philipp Seidl, Philipp Renz, Natalia Dyubankova, Paulo Neves, Jonas Verhoeven, Marwin Segler, Jörg K. Wegner, Sepp Hochreiter, Günter Klambauer
Finding synthesis routes for molecules of interest is an essential step in the discovery of new drugs and materials.
3 code implementations • ICLR 2022 • Krzysztof Maziarz, Henry Jackson-Flux, Pashmina Cameron, Finton Sirockin, Nadine Schneider, Nikolaus Stiefl, Marwin Segler, Marc Brockschmidt
Recent advancements in deep learning-based modeling of molecules promise to accelerate in silico drug discovery.
2 code implementations • 26 Nov 2020 • Benedek Fabian, Thomas Edlich, Héléna Gaspar, Marwin Segler, Joshua Meyers, Marco Fiscato, Mohamed Ahmed
We apply a Transformer architecture, specifically BERT, to learn flexible and high quality molecular representations for drug discovery problems.
no code implementations • ICLR 2018 • Daniel Neil, Marwin Segler, Laura Guasch, Mohamed Ahmed, Dean Plumbley, Matthew Sellwood, Nathan Brown
The design of small molecules with bespoke properties is of central importance to drug discovery.
no code implementations • 31 Jan 2017 • 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.