The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations
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Auto-Encoding Variational Bayes
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Deep Contextualized Word Representations
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Categorical Reparameterization with Gumbel-Softmax
Jang, E., Gu, S., & Poole, B. (2016) · arXiv · doi:10.48550/arxiv.1611.01144 · Cited by 3,616
Innovation in the pharmaceutical industry: New estimates of R&D costs
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Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules
Gómez-Bombarelli, R., Wei, J. N., Duvenaud, D., Hernández-Lobato, J. M., Sánchez-Lengeling, B., Sheberla, D., Aguilera-Iparraguirre, J., Hirzel, T. D., Adams, R. P., & Aspuru-Guzik, A. (2018) · ACS Central Science · doi:10.1021/acscentsci.7b00572 · Cited by 3,106
A Deep Learning Approach to Antibiotic Discovery
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Cited by
A guide to machine learning for biologists
Greener, J. G., Kandathil, S. M., Moffat, L., & Jones, D. T. (2022) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-021-00407-0 · Cited by 2,127
Large language models generate functional protein sequences across diverse families
Madani, A., Krause, B., Greene, E. R., Subramanian, S., Mohr, B. P., Holton, J. M., Olmos, J. L., Xiong, C., Sun, Z. Z., Socher, R., et al. (2023) · Nature Biotechnology · doi:10.1038/s41587-022-01618-2 · Cited by 1,078
Identification of antimicrobial peptides from the human gut microbiome using deep learning
Ma, Y., Guo, Z., Xia, B., Zhang, Y., Liu, X., Yu, Y., Tang, N., Tong, X., Wang, M., Ye, X., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01226-0 · Cited by 490
Pyzer-Knapp, E. O., Pitera, J. W., Staar, P. W. J., Takeda, S., Laino, T., Sanders, D. P., Sexton, J., Smith, J. R., & Curioni, A. (2022) · npj Computational Materials · doi:10.1038/s41524-022-00765-z · Cited by 465
Geometric deep learning on molecular representations
Atz, K., Grisoni, F., & Schneider, G. (2021) · Nature Machine Intelligence · doi:10.1038/s42256-021-00418-8 · Cited by 373
Metadata
- Authors
- Das, P., Sercu, T., Wadhawan, K., Padhi, I., Gehrmann, S., Cipcigan, F., Chenthamarakshan, V., Strobelt, H., dos Santos, C., Chen, P.-Y., Yang, Y. Y., Tan, J. P. K., Hedrick, J., Crain, J., & Mojsilovic, A.
- Venue
- Nature Biomedical Engineering
- Published
- 2021-03-11
- Volume
- 5
- Issue
- 6
- Pages
- 613-623
- ISSN
- 2157-846X (ISSN-L)
- OpenAlex
- W3027325047
- Cited by
- 414
- References
- 12
- FWCI
- 26.99
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations. https://app.cochat.ai/papers/10.1038/s41551-021-00689-x
- The paper
- Das, P., Sercu, T., Wadhawan, K., Padhi, I., Gehrmann, S., Cipcigan, F., Chenthamarakshan, V., Strobelt, H., dos Santos, C., Chen, P.-Y., Yang, Y. Y., Tan, J. P. K., Hedrick, J., Crain, J., & Mojsilovic, A. (2021). Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations. Nature Biomedical Engineering. https://doi.org/10.1038/s41551-021-00689-x
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
