Matteo Aldeghi

15 papers Journal 15
YearRankTypeTitle / Venue / Authors
2025 J jnl
Practically Significant Method Comparison Protocols for Machine Learning in Small Molecule Drug Discovery.
J. Chem. Inf. Model.
Jeremy R. Ash, Cas Wognum, Raquel Rodríguez-Pérez, Matteo Aldeghi, Alan C. Cheng, Djork-Arné Clevert, Ola Engkvist, Cheng Fang, Daniel J. Price, Jacqueline M. Hughes-Oliver, W. Patrick Walters
2024 J jnl
A call for an industry-led initiative to critically assess machine learning for real-world drug discovery.
Nat. Mac. Intell.
Cas Wognum, Jeremy R. Ash, Matteo Aldeghi, Raquel Rodríguez-Pérez, Cheng Fang, Alan C. Cheng, Daniel J. Price, Djork-Arné Clevert, Ola Engkvist, W. Patrick Walters
2022 J jnl
A graph representation of molecular ensembles for polymer property prediction.
CoRR
Matteo Aldeghi, Connor W. Coley
2022 J jnl
Bayesian optimization with known experimental and design constraints for chemistry applications.
CoRR
Riley J. Hickman, Matteo Aldeghi, Florian Häse, Alán Aspuru-Guzik
2022 J jnl
On scientific understanding with artificial intelligence.
CoRR
Mario Krenn, Robert Pollice, Si Yue Guo, Matteo Aldeghi, Alba Cervera-Lierta, Pascal Friederich, Gabriel dos Passos Gomes, Florian Häse, Adrian Jinich, AkshatKumar Nigam, Zhenpeng Yao, Alán Aspuru-Guzik
2022 J jnl
Roughness of Molecular Property Landscapes and Its Impact on Modellability.
J. Chem. Inf. Model.
Matteo Aldeghi, David E. Graff, Nathan C. Frey, Joseph A. Morrone, Edward O. Pyzer-Knapp, Kirk E. Jordan, Connor W. Coley
2022 J jnl
Self-Focusing Virtual Screening with Active Design Space Pruning.
J. Chem. Inf. Model.
David E. Graff, Matteo Aldeghi, Joseph A. Morrone, Kirk E. Jordan, Edward O. Pyzer-Knapp, Connor W. Coley
2022 J jnl
Self-focusing virtual screening with active design space pruning.
CoRR
David E. Graff, Matteo Aldeghi, Joseph A. Morrone, Kirk E. Jordan, Edward O. Pyzer-Knapp, Connor W. Coley
2021 J jnl
Assigning Confidence to Molecular Property Prediction.
CoRR
AkshatKumar Nigam, Robert Pollice, Matthew F. D. Hurley, Riley J. Hickman, Matteo Aldeghi, Naruki Yoshikawa, Seyone Chithrananda, Vincent A. Voelz, Alán Aspuru-Guzik
2021 J jnl
Golem: An algorithm for robust experiment and process optimization.
CoRR
Matteo Aldeghi, Florian Häse, Riley J. Hickman, Isaac Tamblyn, Alán Aspuru-Guzik
2021 J jnl
Olympus: a benchmarking framework for noisy optimization and experiment planning.
Mach. Learn. Sci. Technol.
Florian Häse, Matteo Aldeghi, Riley J. Hickman, Loïc M. Roch, Melodie Christensen, Elena Liles, Jason E. Hein, Alán Aspuru-Guzik
2020 J jnl
Olympus: a benchmarking framework for noisy optimization and experiment planning.
CoRR
Florian Häse, Matteo Aldeghi, Riley J. Hickman, Loïc M. Roch, Melodie Christensen, Elena Liles, Jason E. Hein, Alán Aspuru-Guzik
2020 J jnl
The SAMPL6 SAMPLing challenge: assessing the reliability and efficiency of binding free energy calculations.
J. Comput. Aided Mol. Des.
Andrea Rizzi, Travis Jensen, David R. Slochower, Matteo Aldeghi, Vytautas Gapsys, Dimitris Ntekoumes, Stefano Bosisio, Michail Papadourakis, Niel M. Henriksen, Bert L. de Groot, Zoe Cournia, Alex Dickson, Julien Michel, Michael K. Gilson, Michael R. Shirts, David L. Mobley, John D. Chodera
2017 J jnl
Statistical Analysis on the Performance of Molecular Mechanics Poisson-Boltzmann Surface Area versus Absolute Binding Free Energy Calculations: Bromodomains as a Case Study.
J. Chem. Inf. Model.
Matteo Aldeghi, Michael J. Bodkin, Stefan Knapp, Philip C. Biggin
2016 J jnl
The Fragment Molecular Orbital Method Reveals New Insight into the Chemical Nature of GPCR-Ligand Interactions.
J. Chem. Inf. Model.
Alexander Heifetz, Ewa I. Chudyk, Laura Gleave, Matteo Aldeghi, Vadim Cherezov, Dmitri G. Fedorov, Philip C. Biggin, Michael J. Bodkin