The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Feedback GAN for DNA optimizes protein functions
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Cites
Improved Techniques for Training GANs
Salimans, T., Goodfellow, I., Zaremba, W., Cheung, V., Radford, A., & Chen, X. (2016) · arXiv · doi:10.48550/arxiv.1606.03498 · Cited by 6,965
Benner, S. A., & Sismour, A. M. (2005) · Nature Reviews Genetics · doi:10.1038/nrg1637 · Cited by 834
Recurrent Neural Network Model for Constructive Peptide Design
Müller, A. T., Hiss, J. A., & Schneider, G. (2018) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.7b00414 · Cited by 270
modlAMP: Python for antimicrobial peptides
Müller, A. T., Gabernet, G., Hiss, J. A., & Schneider, G. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx285 · Cited by 215
Cited by
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications
Gui, J., Sun, Z., Wen, Y., Tao, D., & Ye, J. (2023) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2021.3130191 · Cited by 1,231
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
Low-N protein engineering with data-efficient deep learning
Biswas, S., Khimulya, G., Alley, E. C., Esvelt, K. M., & Church, G. M. (2021) · Nature Methods · doi:10.1038/s41592-021-01100-y · Cited by 422
Expanding functional protein sequence spaces using generative adversarial networks
Repecka, D., Jauniskis, V., Karpus, L., Rembeza, E., Rokaitis, I., Zrimec, J., Poviloniene, S., Laurynenas, A., Viknander, S., Abuajwa, W., et al. (2021) · Nature Machine Intelligence · doi:10.1038/s42256-021-00310-5 · Cited by 388
Discovering highly potent antimicrobial peptides with deep generative model HydrAMP
Szymczak, P., Możejko, M., Grzegorzek, T., Jurczak, R., Bauer, M., Neubauer, D., Sikora, K., Michalski, M., Sroka, J., Setny, P., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-36994-z · Cited by 231
Metadata
- Authors
- Gupta, A., & Zou, J.
- Venue
- Nature Machine Intelligence
- Published
- 2019-02-11
- Volume
- 1
- Issue
- 2
- Pages
- 105-111
- ISSN
- 2522-5839 (ISSN-L)
- OpenAlex
- W2913423296
- Cited by
- 203
- References
- 4
- FWCI
- 10.39
- Type
- journal article
- Language
- en
- Open access
- closed
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- Gupta, A., & Zou, J. (2019). Feedback GAN for DNA optimizes protein functions. Nature Machine Intelligence. https://doi.org/10.1038/s42256-019-0017-4
Data sources
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.
