Evidence map›Paper›PMID 19324676›Full record

ReviewJournal of the Royal Society, Interface2009

You're one in a googol: optimizing genes for protein expression.

Mark Welch, Alan Villalobos, Claes Gustafsson, Jeremy Minshull

Abstract readReview
In one paragraph

Review in Journal of the Royal Society, Interface, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed.

  1. Codon-optimization in gene therapy: promises, prospects and challenges.Frontiers in bioengineering and biotechnology · 2024
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Selecting an appropriate method for expressingBiotechnology reports (Amsterdam, Netherlands) · 2017
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Protein purification using PDZ affinity chromatography.Current protocols in protein science · 2015
    Article
  18. Article
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mark WelchDNA 2.0, Inc., 1430 O'Brien Drive, Menlo Park, CA 94025, USA.
Alan Villalobos
Claes Gustafsson
Jeremy Minshull

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A vast number of different nucleic acid sequences can all be translated by the genetic code into the same amino acid sequence. These sequences are not all equally useful however; the exact sequence chosen can have profound effects on the expression of the encoded protein. Despite the importance of protein-coding sequences, there has been little systematic study to identify parameters that affect expression. This is probably because protein expression has largely been tackled on an ad hoc basis in many independent projects: once a sequence has been obtained that yields adequate expression for that project, there is little incentive to continue work on the problem. Synthetic biology may now provide the impetus to transform protein expression folklore into design principles, so that DNA sequences may easily be designed to express any protein in any system. In this review, we offer a brief survey of the literature, outline the major challenges in interpreting existing data and constructing robust design algorithms, and propose a way to proceed towards the goal of rational sequence engineering.

Indexed as

Gene Expression ProfilingAlgorithmsAmino Acid MotifsAmino Acid SequenceBase SequenceBiotechnologyCodonDNAGenetic CodeMolecular Sequence DataOpen Reading FramesProteinsProteomicsSequence AlignmentCodonDNAProteins

Identifiers

PMID19324676
PMCPMC2843954

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.