The DOI matches its Crossref record.
Chematica: A Story of Computer Code That Started to Think like a Chemist
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Items 101–115 of 115
Application of Artificial Intelligence in Biochemistry
Inbavalli., K. (2023) · doi:10.22192/ttdls.2023.015
Ekanayake, A. K., Ekanayake, A. K., & Gupta, N. (2023) · doi:10.22192/ttdls.2023.009
La revolución quimioinformática: enseñándole química a los robots
Bastidas, J. R. M. (2024) · Revista de Química · doi:10.18800/quimica.202401.001
Every atom counts: predicting sites of reaction based on chemistry within two bonds
Lam, C. C., & Goodman, J. M. (2024) · Digital Discovery · doi:10.1039/d4dd00092g
Convergence of machine learning and artificial intelligence in pharmacological implications
Lahkar, R., Kalita, A. J., Kalita, P., Devi, C., & Kalita, P. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-14061-7.00007-5
Hasić, H., & Ishida, T. (2025) · Journal of Cheminformatics · doi:10.1186/s13321-025-01130-0
“Additionally, the emergence of advanced rule-based approaches like Chematica/Synthia [12–14] demonstrated that the consistently expanding body of knowledge could be effectively and efficiently represented and utilized in silico .”
Saigiridharan, L., Hassen, A. K., Lai, H., Torren-Peraire, P., Engkvist, O., & Genheden, S. (2024) · Figshare · doi:10.6084/m9.figshare.26724365
Ree, N., Göller, A. H., & Jensen, J. H. (2021) · Figshare · doi:10.6084/m9.figshare.13978774
Pasquini, M., & Stenta, M. (2024) · Figshare · doi:10.6084/m9.figshare.26579813
(Q)SAR Methods Used in MOF Studies
Visa, A., Pleşu, N., Ilia, G., & Maranescu, B. (2025) · Springer handbooks · doi:10.1007/978-3-031-81728-1_16
Beyond Reaction Data: Learning Chemical Knowledge from Large-Scale Molecules for Retrosynthesis
Chen, Y., Ma, T., Yu, Z., et al. (2026) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3770855.3818972
“Traditional retrosynthesis methods rely on expert intuition and predefined rules [9, 15].”
Zanella, S., Brusa, A., & Carlone, A. (2026) · Chemical Communications · doi:10.1039/d6cc05298c
Line-Graph Node Centrality in Retrosynthesis
Bošković, Ž. (2026) · The Journal of Organic Chemistry · doi:10.1021/acs.joc.6c00934
Intellectual Property and Algoraceutical Invention
Rotino, G. (2026) · Law for professionals · doi:10.1007/978-3-032-38537-6_7
Metadata
- Authors
- Grzybowski, B. A., Szymkuć, S., Gajewska, E. P., Molga, K., Dittwald, P., Wołos, A., & Klucznik, T.
- Venue
- Chem
- Publisher
- Elsevier BV
- Published
- 2018-03
- Volume
- 4
- Issue
- 3
- Pages
- 390-398
- ISSN
- 2451-9294 (ISSN-L)
- OpenAlex
- W2789913372
- Cited by
- 114
- References
- 0
- Citations by year
- 2026: 11 · 2025: 12 · 2024: 19 · 2023: 32 · 2022: 7 · 2021: 15 · 2020: 11 · 2019: 7
- FWCI
- 6.17
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Chem (publishedVersion)
- Scholarworks@UNIST (Ulsan National Institute of Science and Technology) (submittedVersion)
- Funders
- Defense Advanced Research Projects Agency
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Physical Sciences › Computer Science › Artificial Intelligence › AI-based Problem Solving and Planning
- Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
- Keywords
- cheminformatics software, artificial intelligence in chemistry, retrosynthesis
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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