ArticleSynthetic biology (Oxford, England)2018
Advances in
Article in Synthetic biology (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 13 citations in OpenAlex.
- Reaching New Heights in Genetic Code Manipulation with High Throughput Screening.Chemical reviews · 2024Review
- Hyperaccurate Ribosomes for Improved Genetic Code Reprogramming.ACS synthetic biology · 2022Article
- Reprogramming the genetic code.Nature reviews. Genetics · 2021Review
- Expanding the Genetic Code for Neuronal Studies.Chembiochem : a European journal of chemical biology · 2020Review
- Incorporation of non-standard amino acids into proteins: challenges, recent achievements, and emerging applications.Applied microbiology and biotechnology · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To date, various genetic code manipulation methods have been developed to introduce non-proteinogenic amino acids into peptides by translation. However, the number of amino acids that can be used simultaneously remains limited even using these methods. Additionally, the scope of amino acid substrates that are compatible with ribosomal translation systems is also limited. For example, difficult substrates such as d-amino acids and β-amino acids are much less efficiently incorporated into peptides than l-α-amino acids. Here, we focus on three recently developed methodologies that address these issues: (i) artificial division of codon boxes to increase the number of available amino acids, (ii) orthogonal ribosomal translation systems to 'duplicate' the codon table and (iii) development of novel artificial tRNAs that enhance incorporation of difficult amino acid substrates.
Indexed as
Identifiers
What OpenQuestion holds
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.