GenSMILES: An enhanced validity conscious representation for inverse design of molecules
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GenSMILES replaces paired symbols with single-token, position-aware representations.
“To address these issues, GenSMILES5 proposes an alternative representation that replaces paired symbols with single-token, position-aware representations.”
From PCF-VAE: posterior collapse free variational autoencoder for de novo drug design (2025) · cites this paper as [5]
Cites
Quantum chemistry structures and properties of 134 kilo molecules
Ramakrishnan, R., Dral, P. O., Rupp, M., & von Lilienfeld, O. A. (2014) · Scientific Data · doi:10.1038/sdata.2014.22 · Cited by 1,966 · see citing works
Molecular generative model based on conditional variational autoencoder for de novo molecular design
Lim, J., Ryu, S., Kim, J. W., & Kim, W. Y. (2018) · Journal of Cheminformatics · doi:10.1186/s13321-018-0286-7 · Cited by 421 · see citing works
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PCF-VAE: posterior collapse free variational autoencoder for de novo drug design
Bhadwal, A. S., Kumari, M., & Kumar, A. (2025) · Scientific Reports · doi:10.1038/s41598-025-14285-5 · Cited by 7 · see citing works
“Recent years have seen the usefulness of generative deep learning models in several domains such as remote sensing, image analysis, text generation, and molecule design 5–7 .”
Self-citation
- Authors
- Bhadwal, A. S., Kumar, K., & Kumar, N.
- Affiliations
- National Institute of Technology Uttarakhand (IN)
- Chandigarh University (IN)
- Corresponding author
- Bhadwal, Arun Singh
- Venue
- Knowledge-Based Systems
- Publisher
- Elsevier BV
- Published
- 2023-05
- Volume
- 268
- Pages
- 110429
- ISSN
- 0950-7051 (ISSN-L)
- OpenAlex
- W4324102210
- Cited by
- 17
- References
- 2
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 6 · 2023: 2
- FWCI
- 2.43
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Knowledge-Based Systems (publishedVersion)
- 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 › Physical and Theoretical Chemistry › History and advancements in chemistry
- Keywords
- SMILES representation, inverse design, generative molecular design, chemical graph representation, derivation rules, chemical space exploration
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