1 code implementation • ICML 2020 • Sai Krishna Gottipati, Boris Sattarov, Sufeng. Niu, Hao-Ran Wei, Yashaswi Pathak, Shengchao Liu, Simon Blackburn, Karam Thomas, Connor Coley, Jian Tang, Sarath Chandar, Yoshua Bengio
In this work, we propose a novel reinforcement learning (RL) setup for drug discovery that addresses this challenge by embedding the concept of synthetic accessibility directly into the de novo compound design system.
no code implementations • 6 Feb 2024 • Chenqing Hua, Connor Coley, Guy Wolf, Doina Precup, Shuangjia Zheng
Protein-protein interactions (PPIs) are crucial in regulating numerous cellular functions, including signal transduction, transportation, and immune defense.
no code implementations • 8 Jun 2021 • Hangrui Bi, Hengyi Wang, Chence Shi, Connor Coley, Jian Tang, Hongyu Guo
Reliably predicting the products of chemical reactions presents a fundamental challenge in synthetic chemistry.
4 code implementations • 2 Apr 2019 • Kevin Yang, Kyle Swanson, Wengong Jin, Connor Coley, Philipp Eiden, Hua Gao, Angel Guzman-Perez, Timothy Hopper, Brian Kelley, Miriam Mathea, Andrew Palmer, Volker Settels, Tommi Jaakkola, Klavs Jensen, Regina Barzilay
In addition, we introduce a graph convolutional model that consistently matches or outperforms models using fixed molecular descriptors as well as previous graph neural architectures on both public and proprietary datasets.
Ranked #3 on Molecular Property Prediction on QM9
no code implementations • ICLR 2018 • Benson Chen, Connor Coley, Regina Barzilay, Tommi Jaakkola
Deep learning algorithms are increasingly used in modeling chemical processes.