ArticleNature methods2016
Predictable tuning of protein expression in bacteria.
Article in Nature methods, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
65 citing papers in PubMed.
- Host-aware Identification of Intrinsic Gene Expression Biopart Parameters using Combinatorial Libraries.Nature communications · 2026Article
- Inference of fitness landscapes with heterogeneous patterns of epistasis across sites.bioRxiv : the preprint server for biology · 2026Article
- Fine modulation of carbon flow in central carbon metabolism via ribosome-binding site modification inMetabolic engineering communications · 2026Article
- Activity-Cloud Organization of Shine-Dalgarno Sequences to Guide Translation Engineering inACS omega · 2026Article
- Inference and Visualization of Complex Genotype-Phenotype Maps.Molecular biology and evolution · 2026Article
- Inference and visualization of complex genotype-phenotype maps withbioRxiv : the preprint server for biology · 2025Article
- Polypeptides synthesized by common bacteria in the human gut improve rodent metabolism.Nature microbiology · 2025Article
- Establishing Halomonas as a chassis for industrial biotechnology: advances in synthetic biology tool development and metabolic engineering strategies.Microbial cell factories · 2025Review
- The knowledge driven DBTL cycle provides mechanistic insights while optimising dopamine production in Escherichia coli.Microbial cell factories · 2025Article
- Innovations, Challenges and Future Directions of T7RNA Polymerase in Microbial Cell Factories.ACS synthetic biology · 2025Review
- Transfer learning for cross-context prediction of protein expression from 5'UTR sequence.Nucleic acids research · 2024Article
- Combinatorial optimization of gene expression through recombinase-mediated promoter and terminator shuffling in yeast.Nature communications · 2024Article
- Using design of experiments to guide genetic optimization of engineered metabolic pathways.Journal of industrial microbiology & biotechnology · 2024Review
- Design of an effective small expression tag to enhance GPCR production in E. coli-based cell-free and whole cell expression systems.Protein science : a publication of the Protein Society · 2023Article
- Development of a Tetracycline-Inducible System for Conditional Gene Expression in Lactococcus lactis and Streptococcus thermophilus.Microbiology spectrum · 2023Article
- Effective design and inference for cell sorting and sequencing based massively parallel reporter assays.Bioinformatics (Oxford, England) · 2023Article
- Ultradeep characterisation of translational sequence determinants refutes rare-codon hypothesis and unveils quadruplet base pairing of initiator tRNA and transcript.Nucleic acids research · 2023Article
- Advancing reproducibility can ease the 'hard truths' of synthetic biology.Synthetic biology (Oxford, England) · 2023Review
- Precision engineering of biological function with large-scale measurements and machine learning.PloS one · 2023Article
- Efficient Bacterial Genome Engineering throughout the Central Dogma Using the Dual-Selection MarkerACS synthetic biology · 2022Article
5 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
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We comprehensively assessed the contribution of the Shine-Dalgarno sequence to protein expression and used the data to develop EMOPEC (Empirical Model and Oligos for Protein Expression Changes; http://emopec.biosustain.dtu.dk). EMOPEC is a free tool that makes it possible to modulate the expression level of any Escherichia coli gene by changing only a few bases. Measured protein levels for 91% of our designed sequences were within twofold of the desired target level.
Indexed as
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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.