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Metabolic engineering of recombinant protein secretion by Saccharomyces cerevisiae

2012· review· en· W1980754871 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFEMS Yeast Research · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFungal and yeast genetics research
Canadian institutionsnot available
FundersNational Institutes of HealthFondation ChalmersNational Institute of General Medical SciencesKnut och Alice Wallenbergs Stiftelse
KeywordsSecretionSaccharomyces cerevisiaeContext (archaeology)BiologyMetabolic engineeringHeterologousSynthetic biologyYeastSecretory proteinSystems biologyProtein engineeringComputational biologyProtein biosynthesisProtein foldingBiochemical engineeringCell biologyBiochemistryEngineeringGeneEnzyme

Abstract

fetched live from OpenAlex

The yeast Saccharomyces cerevisiae is a widely used cell factory for the production of fuels and chemicals, and it is also provides a platform for the production of many heterologous proteins of medical or industrial interest. Therefore, many studies have focused on metabolic engineering S. cerevisiae to improve the recombinant protein production, and with the development of systems biology, it is interesting to see how this approach can be applied both to gain further insight into protein production and secretion and to further engineer the cell for improved production of valuable proteins. In this review, the protein post-translational modification such as folding, trafficking, and secretion, steps that are traditionally studied in isolation will here be described in the context of the whole system of protein secretion. Furthermore, examples of engineering secretion pathways, high-throughput screening and systems biology applications of studying protein production and secretion are also given to show how the protein production can be improved by different approaches. The objective of the review is to describe individual biological processes in the context of the larger, complex protein synthesis network.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.976
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.071
GPT teacher head0.363
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it