ArticleNature communications2020
Model-driven generation of artificial yeast promoters.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers.
What it found
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Who cites it
79 citing papers in PubMed, 145 citations in OpenAlex.
- Upcycling Vegetable Waste Into Functional Food Ingredients via Synergistic Microbial Engineering and Artificial Intelligence.Comprehensive reviews in food science and food safety · 2026Review
- Yeast species resource exploration and application in cell factories.Synthetic and systems biotechnology · 2026Review
- Advances in Key Genetic Elements and Strategies for High-Yield Heterologous Protein Expression inJournal of fungi (Basel, Switzerland) · 2026Review
- Opportunities for artificial intelligence and synthetic biology in designing living drug delivery systems.Advanced drug delivery reviews · 2026Review
- Context-aware synthetic promoter design using neural networks enables rewiring of eukaryotic transcriptional networks.NPJ systems biology and applications · 2026Article
- Design prokaryotic cis-regulatory elements using language model.Nucleic acids research · 2026Article
- Synthetic Biology of Plants and Microbes for Agriculture, Environment, and Future Applications.Chemical reviews · 2026Review
- Biological parts in yeast synthetic biology: from regulatory elements to predictive design platforms.FEMS yeast research · 2026Review
- Synthetic promoters developed through a site-specific integration system enhance antibody expression in fed-batch culture.Engineering in life sciences · 2026Article
- Benchmarking the PAM compatibility of Cas12a variants for high-throughput yeast genetic variant engineering.Applied and environmental microbiology · 2025Article
- Synthetic tunable promoters for flexible control of multi-gene expression in mammalian cells.Journal of advanced research · 2025Article
- Deep learning guided programmable design of Escherichia coli core promoters from sequence architecture to strength control.Nucleic acids research · 2025Article
- Learning the sequence code of protein expression in human immune cells.Science advances · 2025Article
- De novo design of insulated cis-regulatory elements based on deep learning-predicted fitness landscape.Nucleic acids research · 2025Article
- The design and engineering of synthetic genomes.Nature reviews. Genetics · 2025Review
- Advancing cellulose utilization and engineering consolidated bioprocessing yeasts: current state and perspectives.Applied microbiology and biotechnology · 2025Review
- Integrating yeast biodiversity and machine learning for predictive metabolic engineering.FEMS yeast research · 2025Review
- Improving the generalization of protein expression models with mechanistic sequence information.Nucleic acids research · 2025Article
- Optimization of regulatory DNA with active learning.Computational and structural biotechnology journal · 2025Article
- Designing strong inducible synthetic promoters in yeasts.Nature communications · 2024Article
19 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Promoters play a central role in controlling gene regulation; however, a small set of promoters is used for most genetic construct design in the yeast Saccharomyces cerevisiae. Generating and utilizing models that accurately predict protein expression from promoter sequences would enable rapid generation of useful promoters and facilitate synthetic biology efforts in this model organism. We measure the gene expression activity of over 675,000 sequences in a constitutive promoter library and over 327,000 sequences in an inducible promoter library. Training an ensemble of convolutional neural networks jointly on the two data sets enables very high (R
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.