ArticleNature structural & molecular biology2018
Accurate design of translational output by a neural network model of ribosome distribution.
Article in Nature structural & molecular biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.
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Who cites it
61 citing papers in PubMed.
- Systematic optimization ofEngineering microbiology · 2026Review
- Halting translation by the letter with sequence-selective small molecules.Nature chemical biology · 2026Review
- VeloHARMO: a deep learning framework for mRNA coding sequence generation and design via translation velocity harmonization.Briefings in bioinformatics · 2026Article
- The Tor pathway, ribosome concentration, and wobble decoding mediate inhibitory effects of the Leu-Pro CUC-CCG codon pair inRNA (New York, N.Y.) · 2026Article
- Inferring translational efficiency from transcriptomes improves noncanonical neoantigen prioritization and cancer patient stratification.NPJ precision oncology · 2026Article
- The importance of nonsense errors: Estimating the rates and implications of ribosome drop-off during protein synthesis.PLoS genetics · 2026Article
- Predicting the translation efficiency of messenger RNA in mammalian cells.Nature biotechnology · 2026Article
- Cross-species gene redesign leveraging ortholog information and generative modeling.Nature communications · 2026Article
- Accelerate the Highly Efficient Development of mRNA Vaccines Through Advanced Computational Methods.MedComm · 2026Review
- Conditional deep learning model reveals translation elongation determinants during amino acid deprivation.Communications biology · 2025Article
- Suboptimal codon pairs trigger ribosome collisions and cellular quality control responses in tRNA modification mutants.Nucleic acids research · 2025Article
- Evo-Inspired Engineering of Radical Phenotypes and Emergent Traits.Integrative and comparative biology · 2025Review
- Ageing-related decline of translation as a consequence of transcription dysregulation.Journal of the Royal Society, Interface · 2025Article
- Protein language models reveal evolutionary constraints on synonymous codon choice.bioRxiv : the preprint server for biology · 2025Article
- A generative language model decodes contextual constraints on codon choice for mRNA design.bioRxiv : the preprint server for biology · 2025Article
- Precise measurement of molecular phenotypes with barcode-based CRISPRi systems.Genome biology · 2025Article
- Unveiling the regulatory role of GRP7 in ABA signal-mediated mRNA translation efficiency regulation.Nature communications · 2025Article
- Analysis of RNA translation with a deep learning architecture provides new insight into translation control.Nucleic acids research · 2025Article
- A deep learning model trained on expressed transcripts across different tissue types reveals cell-type codon-optimization preferences.Nucleic acids research · 2025Article
- Improved precision, sensitivity, and adaptability of ordered two-template relay cDNA library preparation for RNA sequencing.RNA (New York, N.Y.) · 2025Article
1 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
Abstract
Synonymous codon choice can have dramatic effects on ribosome speed and protein expression. Ribosome profiling experiments have underscored that ribosomes do not move uniformly along mRNAs. Here, we have modeled this variation in translation elongation by using a feed-forward neural network to predict the ribosome density at each codon as a function of its sequence neighborhood. Our approach revealed sequence features affecting translation elongation and characterized large technical biases in ribosome profiling. We applied our model to design synonymous variants of a fluorescent protein spanning the range of translation speeds predicted with our model. Levels of the fluorescent protein in budding yeast closely tracked the predicted translation speeds across their full range. We therefore demonstrate that our model captures information determining translation dynamics in vivo; that this information can be harnessed to design coding sequences; and that control of translation elongation alone is sufficient to produce large quantitative differences in protein output.
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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.