For the most up-to-date list of publications and citation metrics, check out our Google Scholar.
2024
link Westerlund, Annie M. et al. (2024) "Do Chemformers dream of organic matter? Evaluating a transformer model for multi-step retrosynthesis." J. Chem. Inf. Model. ASAP.
2023
link Westerlund, Annie M. et al. (2023) "Do Chemformers dream of organic matter? Evaluating a transformer model for multi-step retrosynthesis." ChemRxiv.
link Mercado, RocĆo et al. (2023) "Data sharing in chemistry: lessons learned and a case for mandating structured reaction data." J. Chem. Inf. Model. 63, 14, 4253ā4265.
2022
link Nori, Divya et al. (2022) "De novo PROTAC design using graph-based deep generative models." NeurIPS 2022 AI4Science Workshop.
link Romeo Atance, Sara et al. (2022) "De novo drug design using reinforcement learning with graph-based deep generative models." J. Chem. Inf. Model. 62(20), 4863ā4872.
2021
link Gao, Wenhao et al. (2022) "Amortized tree generation for bottom-up synthesis planning and synthesizable molecular design." ICLR 2022.
link Viguera Diez, Juan et al. (2021) "A transferable Boltzmann generator for small-molecule conformers." ELLIS ML4Molecules.
link Mercado, RocĆo et al. (2021) "Exploring graph traversal algorithms in graph-based molecular generation." J. Chem. Inf. Model.
link Gao, Wenhao et al. (2021) "Amortized tree generation for bottom-up synthesis planning and synthesizable molecular design." arXiv.
link Romeo Atance, Sara et al. (2021) "De novo drug design using reinforcement learning with graph-based deep generative models." ChemRxiv.
link Mercado, RocĆo et al. (2021) "Exploring graph traversal algorithms in graph-based molecular generation." ChemRxiv.
link Zhang, Jie et al. (2021). "Comparative study of deep generative models on chemical space coverage." J. Chem. Inf. Model. 61, 6, 2572ā2581.
2020
link Mercado, RocĆo et al. (2020). "Practical notes on building molecular graph generative models." Applied AI Letters.
link Mercado, RocĆo et al. (2020). "Graph networks for molecular design." Mach. Learn.: Sci. Technol.
link Zhang, Jie et al. (2020). "Comparative study of deep generative models on chemical space coverage." ChemRxiv.
link Mercado, RocĆo. (2020). "Using GraphINVENT to generate novel DRD2 actives." Cheminformania.
link David, Laurianne et al. (2020). "Molecular representations in AI-driven drug discovery: a review and practical guide." J. Cheminf. 12(56).
link Mercado, RocĆo et al. (2020). "Practical notes on building molecular graph generative models." ChemRxiv.
link Mercado, RocĆo et al. (2020). "Graph networks for molecular design." ChemRxiv.
2019
link Witherspoon, Velencia J. et al. (2019). "Combined nuclear magnetic resonance and molecular dynamics study of methane adsorption in M2(dobdc) metalāorganic frameworks." J. Phys. Chem. C. 123(19). 12286-12295.
2018
link Braun, Efrem et al. (2018). "Generating carbon schwarzites via zeolite-templating." PNAS. 115(35). E8116-E8124.
link Mercado, RocĆo et al. (2018). "In silico design of 2D and 3D covalent organic frameworks for methane storage applications." Chem. Mater. 30(15). 5069-5086.
link Forse, Alexander C. et al. (2018). "Unexpected diffusion anisotropy of carbon dioxide in the metalāorganic framework Zn2(dobpdc)." J. Am. Chem. Soc. 140(5). 1663-1673.
2016
link Mercado, RocĆo et al. (2016). "Force field development from periodic density functional theory calculations for gas separation applications using metalāorganic frameworks." J. Phys. Chem. C. 120(23). 12590-12604.
2015
link Xiang, Zhonghua et al. (2015). "Systematic tuning and multifunctionalization of covalent organic polymers for enhanced carbon capture." J. Am. Chem. Soc. 137(41). 13301-13307.
link Simon, Cory M. et al. (2015). "Computer-aided search for materials to store natural gas for vehicles." Front. Young Minds. 3-11.
link Simon, Cory M. et al. (2015). "What are the best materials to separate a xenon/krypton mixture?" Chem. Mater. 27(12). 4459-4475.
link Simon, Cory M. et al. (2015). "The materials genome in action: identifying the performance limits for methane storage." Energy Environ. Sci. 8. 1190-1199.