From 0990d85b299f36a19f4cdcf50fca2817e71bc6bf Mon Sep 17 00:00:00 2001 From: albert bou Date: Tue, 6 Aug 2024 11:02:55 +0200 Subject: [PATCH] update README --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 3188c07..e74466b 100644 --- a/README.md +++ b/README.md @@ -8,6 +8,8 @@ ![license](https://img.shields.io/badge/license-MIT-blue) [![tutorials](https://img.shields.io/badge/tutorials-available-brightgreen)](https://github.com/Acellera/acegen-open/tree/main/tutorials) ![python](https://img.shields.io/badge/python-3.9%20|%203.10%20|%203.11-blue) +[![arXiv](https://img.shields.io/badge/arXiv--blue)](https://arxiv.org/abs/2405.04657) +[![JCIM](https://img.shields.io/badge/JCIM-DOI-blue)](https://pubs.acs.org/doi/abs/10.1021/acs.jcim.4c00895) --- @@ -15,8 +17,6 @@ ACEGEN is a comprehensive toolkit designed to leverage reinforcement learning (RL) techniques for generative chemistry tasks, particularly in drug design. ACEGEN harnesses the capabilities of TorchRL, a modern library for general decision-making tasks, to provide a flexible and integrated solution for generative drug design challenges. -The full paper can be found [here](https://pubs.acs.org/doi/abs/10.1021/acs.jcim.4c00895). - --- ## Key Features