1 code implementation • 11 Oct 2024 • Benson Chen, Tomasz Danel, Patrick J. McEnaney, Nikhil Jain, Kirill Novikov, Spurti Umesh Akki, Joshua L. Turnbull, Virja Atul Pandya, Boris P. Belotserkovskii, Jared Bryce Weaver, Ankita Biswas, Dat Nguyen, Gabriel H. S. Dreiman, Mohammad Sultan, Nathaniel Stanley, Daniel M Whalen, Divya Kanichar, Christoph Klein, Emily Fox, R. Edward Watts
DNA-Encoded Libraries (DEL) are combinatorial small molecule libraries that offer an efficient way to characterize diverse chemical spaces.
no code implementations • 20 Oct 2023 • Benson Chen, Mohammad M. Sultan, Theofanis Karaletsos
DNA-Encoded Library (DEL) has proven to be a powerful tool that utilizes combinatorially constructed small molecules to facilitate highly-efficient screening assays.
1 code implementation • 30 Nov 2022 • Kirill Shmilovich, Benson Chen, Theofanis Karaletsos, Mohammad M. Sultan
Computational models have been deployed to learn the latent binding affinities that are correlated to the sequenced count data; however, this correlation is often obfuscated by various sources of noise introduced in its complicated data-generation process.
no code implementations • NeurIPS Workshop AI4Scien 2021 • Benson Chen, Xiang Fu, Regina Barzilay, Tommi Jaakkola
Equipped with the learned fragment vocabulary, we propose Fragment-based Sequential Translation (FaST), which learns a reinforcement learning (RL) policy to iteratively translate model-discovered molecules into increasingly novel molecules while satisfying desired properties.
2 code implementations • 8 Jun 2020 • Benson Chen, Gary Bécigneul, Octavian-Eugen Ganea, Regina Barzilay, Tommi Jaakkola
Current graph neural network (GNN) architectures naively average or sum node embeddings into an aggregated graph representation -- potentially losing structural or semantic information.
Ranked #1 on
Drug Discovery
on BBBP
no code implementations • 21 Oct 2019 • Benson Chen, Tianxiao Shen, Tommi S. Jaakkola, Regina Barzilay
We propose a new model for making generalizable and diverse retrosynthetic reaction predictions.
2 code implementations • 29 May 2019 • Benson Chen, Regina Barzilay, Tommi Jaakkola
Much of the recent work on learning molecular representations has been based on Graph Convolution Networks (GCN).
no code implementations • ICLR 2018 • Benson Chen, Connor Coley, Regina Barzilay, Tommi Jaakkola
Deep learning algorithms are increasingly used in modeling chemical processes.