The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Burden-driven feedback control of gene expression
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Citations
Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
Edgar, R. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.207 · Cited by 13,288
RNA-Seq: a revolutionary tool for transcriptomics
Wang, Z., Gerstein, M., & Snyder, M. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2484 · Cited by 13,174
Synthetic spike-in standards for RNA-seq experiments
Jiang, L., Schlesinger, F., Davis, C. A., Zhang, Y., Li, R., Salit, M., Gingeras, T. R., & Oliver, B. (2011) · Genome Research · doi:10.1101/gr.121095.111 · Cited by 653
The bioenergetic costs of a gene
Lynch, M., & Marinov, G. K. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1514974112 · Cited by 600
Bremer, H., & Dennis, P. P. (2008) · EcoSal Plus · doi:10.1128/ecosal.5.2.3 · Cited by 539
Cited by
Microbiome and Human Health: Current Understanding, Engineering, and Enabling Technologies
Aggarwal, N., Kitano, S., Puah, G. R. Y., Kittelmann, S., Hwang, I. Y., & Chang, M. W. (2023) · Chemical Reviews · doi:10.1021/acs.chemrev.2c00431 · Cited by 508
Engineering bacteria for diagnostic and therapeutic applications
Riglar, D. T., & Silver, P. A. (2018) · Nature Reviews Microbiology · doi:10.1038/nrmicro.2017.172 · Cited by 460
Materials design by synthetic biology
Tang, T.-C., An, B., Huang, Y., Vasikaran, S., Wang, Y., Jiang, X., Lu, T. K., & Zhong, C. (2020) · Nature Reviews Materials · doi:10.1038/s41578-020-00265-w · Cited by 386
A universal biomolecular integral feedback controller for robust perfect adaptation
Aoki, S. K., Lillacci, G., Gupta, A., Baumschlager, A., Schweingruber, D., & Khammash, M. (2019) · Nature · doi:10.1038/s41586-019-1321-1 · Cited by 355
Bervoets, I., & Charlier, D. (2019) · FEMS Microbiology Reviews · doi:10.1093/femsre/fuz001 · Cited by 180
Modeling host–pathway dynamics at the genome scale with machine learning
Merzbacher, C., Mac Aodha, O., & Oyarzún, D. A. (2025) · Metabolic Engineering · doi:10.1016/j.ymben.2025.05.008 · Cited by 13
Hands-On Growth Laws Theory Cookbook
Droghetti, R., Corigliano, M., Calabrese, L., Fuchs, P., Vaidyanathan, A., Keisers, J., Micali, G., Lagomarsino, M. C., & Ciandrini, L. (2026) · PRX Life · doi:10.1103/x33x-srz4 · Cited by 5
Metadata
- Authors
- Ceroni, F., Boo, A., Furini, S., Gorochowski, T. E., Borkowski, O., Ladak, Y. N., Awan, A. R., Gilbert, C., Stan, G.-B., & Ellis, T.
- Venue
- Nature Methods
- Published
- 2018-03-26
- Volume
- 15
- Issue
- 5
- Pages
- 387-393
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2747801569
- Cited by
- 372
- References
- 6
- FWCI
- 12.48
- Type
- journal article
- Language
- en
- Open access
- green
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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.
