Generative molecular design in low data regimes
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Mature software tools now exist to run generative models on conventional computers, and community-accepted benchmarks enable systematic assessment of generated small molecules considering predicted activity, novelty, validity, and diversity.
“Mature software tools now exist to run generative models on conventional computers,154,157 and community-accepted benchmarks enable the systematic assessment of generated small-molecules, considering not only their predicted activity but also their novelty, validity, and diversity.158,159”
From Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence (2023) · cites this paper as [157]
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- Authors
- Moret, M., Friedrich, L., Grisoni, F., Merk, D., & Schneider, G.
- Affiliations
- ETH Zurich (CH)
- Goethe University Frankfurt (DE)
- Corresponding author
- Schneider, Gisbert
- Venue
- Nature Machine Intelligence
- Published
- 2020-03-16
- Volume
- 2
- Issue
- 3
- Pages
- 171-180
- ISSN
- 2522-5839 (ISSN-L)
- OpenAlex
- W3011286504
- Cited by
- 219
- References
- 45
- Citations by year
- 2026: 31 · 2025: 31 · 2024: 45 · 2023: 33 · 2022: 36 · 2021: 33 · 2020: 10
- FWCI
- 13.91
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nature Machine Intelligence (publishedVersion)
- Funders
- Novartis Foundation (FreeNovation: AI in Drug Discovery)
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (205321_182176)
- RETHINK initiative at ETH Zurich
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
- Physical Sciences › Chemistry › Organic Chemistry › Synthesis and Characterization of Heterocyclic Compounds
- Keywords
- generative molecular design, de novo molecule generation, low-data regimes, compound library generation, chemical space exploration, drug-like molecules, natural products, bioactive compounds, open source software
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