| Molecular representations in AI-driven drug discovery: a review and practical guide L David, A Thakkar, R Mercado, O Engkvist Journal of Cheminformatics 12 (1), 56, 2020 | 436 | 2020 |
| The materials genome in action: identifying the performance limits for methane storage CM Simon, J Kim, DA Gomez-Gualdron, JS Camp, YG Chung, RL Martin, ... Energy & Environmental Science 8 (4), 1190-1199, 2015 | 384 | 2015 |
| What are the best materials to separate a xenon/krypton mixture? CM Simon, R Mercado, SK Schnell, B Smit, M Haranczyk Chemistry of Materials 27 (12), 4459-4475, 2015 | 267 | 2015 |
| Systematic tuning and multifunctionalization of covalent organic polymers for enhanced carbon capture Z Xiang, R Mercado, JM Huck, H Wang, Z Guo, W Wang, D Cao, ... Journal of the American Chemical Society 137 (41), 13301-13307, 2015 | 224 | 2015 |
| Graph networks for molecular design R Mercado, T Rastemo, E Lindelöf, G Klambauer, O Engkvist, H Chen, ... Machine Learning: Science and Technology 2 (2), 025023, 2021 | 189 | 2021 |
| In silico design of 2D and 3D covalent organic frameworks for methane storage applications R Mercado, RS Fu, AV Yakutovich, L Talirz, M Haranczyk, B Smit Chemistry of Materials 30 (15), 5069-5086, 2018 | 145 | 2018 |
| Generating carbon schwarzites via zeolite-templating E Braun, Y Lee, SM Moosavi, S Barthel, R Mercado, IA Baburin, ... Proceedings of the National Academy of Sciences 115 (35), E8116-E8124, 2018 | 135 | 2018 |
| Force field development from periodic density functional theory calculations for gas separation applications using metal–organic frameworks R Mercado, B Vlaisavljevich, LC Lin, K Lee, Y Lee, JA Mason, DJ Xiao, ... The Journal of Physical Chemistry C 120 (23), 12590-12604, 2016 | 115 | 2016 |
| Unexpected Diffusion Anisotropy of Carbon Dioxide in the Metal–Organic Framework Zn2(dobpdc) AC Forse, MI Gonzalez, RL Siegelman, VJ Witherspoon, S Jawahery, ... Journal of the American Chemical Society 140 (5), 1663-1673, 2018 | 81 | 2018 |
| De Novo Drug Design Using Reinforcement Learning with Graph-Based Deep Generative Models SR Atance, JV Diez, O Engkvist, S Olsson, R Mercado Journal of chemical information and modeling 62 (20), 4863-4872, 2022 | 76 | 2022 |
| Amortized tree generation for bottom-up synthesis planning and synthesizable molecular design W Gao, R Mercado, CW Coley arXiv preprint arXiv:2110.06389, 2021 | 56 | 2021 |
| Comparative study of deep generative models on chemical space coverage J Zhang, R Mercado, O Engkvist, H Chen Journal of Chemical Information and Modeling 61 (6), 2572-2581, 2021 | 56 | 2021 |
| Practical notes on building molecular graph generative models R Mercado, T Rastemo, E Lindelöf, G Klambauer, O Engkvist, H Chen, ... Applied AI Letters 1 (2), 2020 | 25 | 2020 |
| Combined Nuclear Magnetic Resonance and Molecular Dynamics Study of Methane Adsorption in M2(dobdc) Metal–Organic Frameworks VJ Witherspoon, R Mercado, E Braun, A Mace, J Bachman, JR Long, ... The Journal of Physical Chemistry C 123 (19), 12286-12295, 2019 | 19 | 2019 |
| Data sharing in chemistry: lessons learned and a case for mandating structured reaction data R Mercado, SM Kearnes, CW Coley Journal of Chemical Information and Modeling 63 (14), 4253-4265, 2023 | 16 | 2023 |
| De novo PROTAC design using graph-based deep generative models D Nori, CW Coley, R Mercado arXiv preprint arXiv:2211.02660, 2022 | 15 | 2022 |
| Exploring graph traversal algorithms in graph-based molecular generation R Mercado, EJ Bjerrum, O Engkvist Journal of Chemical Information and Modeling 62 (9), 2093-2100, 2021 | 15 | 2021 |
| Do Chemformers Dream of Organic Matter? Evaluating a Transformer Model for Multistep Retrosynthesis AM Westerlund, S Manohar Koki, S Kancharla, A Tibo, L Saigiridharan, ... Journal of Chemical Information and Modeling 64 (8), 3021-3033, 2024 | 3 | 2024 |
| Computer-aided search for materials to store natural gas for vehicles CM Simon, J Kim, DA Gomez-Gualdron, YG Chung, RL Martin, ... Front. Young Minds 3 (11.10), 3389, 2015 | 3 | 2015 |
| Modeling PROTAC degradation activity with machine learning S Ribes, E Nittinger, C Tyrchan, R Mercado Artificial Intelligence in the Life Sciences, 100105, 2024 | | 2024 |
