| Self-Referencing Embedded Strings (SELFIES): A 100% robust molecular string representation M Krenn, F Hase, AK Nigam, P Friederich, A Aspuru-Guzik Machine Learning: Science and Technology, 2020 | 939 | 2020 |
| Data-driven strategies for accelerated materials design R Pollice, G dos Passos Gomes, M Aldeghi, RJ Hickman, M Krenn, ... Accounts of Chemical Research 54 (4), 849-860, 2021 | 329 | 2021 |
| On scientific understanding with artificial intelligence M Krenn, R Pollice, SY Guo, M Aldeghi, A Cervera-Lierta, P Friederich, ... Nature Reviews Physics 4 (12), 761-769, 2022 | 254 | 2022 |
| A comprehensive discovery platform for organophosphorus ligands for catalysis T Gensch, G dos Passos Gomes, P Friederich, E Peters, T Gaudin, ... Journal of the American Chemical Society, 2021 | 216 | 2021 |
| Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space AK Nigam, P Friederich, M Krenn, A Aspuru-Guzik International Conference on Learning Representations (ICLR)., 2020 | 162 | 2020 |
| Beyond generative models: superfast traversal, optimization, novelty, exploration and discovery (STONED) algorithm for molecules using SELFIES AK Nigam, R Pollice, M Krenn, G dos Passos Gomes, A Aspuru-Guzik Chemical science 12 (20), 7079-7090, 2021 | 156 | 2021 |
| SELFIES and the future of molecular string representations M Krenn, Q Ai, S Barthel, N Carson, A Frei, NC Frey, P Friederich, ... Patterns 3 (10), 2022 | 150 | 2022 |
| Parallel tempered genetic algorithm guided by deep neural networks for inverse molecular design AK Nigam, R Pollice, A Aspuru-Guzik Digital Discovery 1 (4), 390-404, 2022 | 79* | 2022 |
| Assigning confidence to molecular property prediction AK Nigam, R Pollice, MFD Hurley, RJ Hickman, M Aldeghi, N Yoshikawa, ... Expert opinion on drug discovery 16 (9), 1009-1023, 2021 | 59 | 2021 |
| Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning LA Thiede, M Krenn, AK Nigam, A Aspuru-Guzik Machine Learning: Science and Technology 3 (3), 035008, 2020 | 49* | 2020 |
| Tartarus: A benchmarking platform for realistic and practical inverse molecular design AK Nigam, R Pollice, G Tom, K Jorner, LA Thiede, A Kundaje, ... 37th Conference on Neural Information Processing Systems (NeurIPS 2023 …, 2023 | 32 | 2023 |
| Deciphering the impact of genomic variation on function Code of Conduct Committee (alphabetical by last name) Cody Sarah 33 Farrell ... Nature 633 (8028), 47-57, 2024 | 20* | 2024 |
| Artificial design of organic emitters via a genetic algorithm enhanced by a deep neural network AK Nigam, R Pollice, P Friederich, A Aspuru-Guzik Chemical Science 15 (7), 2618-2639, 2024 | 16 | 2024 |
| Virtualflow 2.0-the next generation drug discovery platform enabling adaptive screens of 69 billion molecules C Gorgulla, AK Nigam, M Koop, S Selim Çınaroğlu, C Secker, ... bioRxiv, 2023.04. 25.537981, 2023 | 13 | 2023 |
| Recent advances in the Self-Referencing Embedding Strings (SELFIES) library A Lo, R Pollice, AK Nigam, AD White, M Krenn, A Aspuru-Guzik Digital Discovery 2, 897-908, 2023 | 12* | 2023 |
| Quantum-computing-enhanced algorithm unveils potential KRAS inhibitors M Ghazi Vakili, C Gorgulla, J Snider, AK Nigam, D Bezrukov, D Varoli, ... Nature Biotechnology, 1-6, 2025 | 10* | 2025 |
| An SLC12A9-dependent ion transport mechanism maintains lysosomal osmolarity R Levin-Konigsberg, K Mitra, K Spees, AK Nigam, K Liu, C Januel, ... Developmental Cell 60 (2), 220-235. e7, 2025 | 7* | 2025 |
| Application of established computational techniques to identify potential SARS-CoV-2 Nsp14-MTase inhibitors in low data regimes AK Nigam, MFD Hurley, F Li, E Konkoľová, M Klíma, J Trylčová, R Pollice, ... Digital Discovery, 2024 | 4* | 2024 |
| Assessing multi-objective optimization of molecules with genetic algorithms against relevant baselines N Kusanda, G Tom, R Hickman, AK Nigam, K Jorner, A Aspuru-Guzik AI for Accelerated Materials Design NeurIPS 2022 Workshop, 2022 | 3 | 2022 |
| Exploring the chemical space without bias: data-free molecule generation with DQN and SELFIES T Gaudin, AK Nigam, A Aspuru-Guzik NeurIPS-2019 MLPS Workshop, 0 | 3* | |
Alan Aspuru-GuzikProfessor of Chemistry and Computer Science, University of Toronto (starting July 1, 2018)Email verificata su utoronto.ca