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Record W2047584624 · doi:10.1002/iub.256

Fluorescent proteins for live cell imaging: Opportunities, limitations, and challenges

2009· review· en· W2047584624 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIUBMB Life · 2009
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsAequorea victoriaGreen fluorescent proteinFluorescenceFluorescent proteinChromophoreCyanFörster resonance energy transferLive cell imagingProtein tagComputational biologyBiologyNanotechnologyBiophysicsChemistryCell biologyBiochemistryCellRecombinant DNAGeneMaterials sciencePhysics

Abstract

fetched live from OpenAlex

The green fluorescent protein (GFP) from the jellyfish Aequorea victoria can be used as a genetically encoded fluorescence marker due to its autocatalytic formation of the chromophore. In recent years, numerous GFP-like proteins with emission colors ranging from cyan to red were discovered in marine organisms. Their diverse molecular properties enabled novel approaches in live cell imaging but also impose certain limitations on their applicability as markers. In this review, we give an overview of key structural and functional properties of fluorescent proteins that should be considered when selecting a marker protein for a particular application and also discuss challenges that lie ahead in the further optimization of the glowing probes.

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)0.000
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 score0.989
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.154
GPT teacher head0.341
Teacher spread0.187 · 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