MétaCan
Menu
Back to cohort
Record W2306469609 · doi:10.1007/978-1-61779-992-1_24

Multicolor Fluorescent In Situ mRNA Hybridization (FISH) on Whole Mounts and Sections

2012· article· en· W2306469609 on OpenAlexaff
Robert Lea, Boyan Bonev, Eamon Dubaissi, Peter D. Vize, Nancy Papalopulu

Bibliographic record

VenueMethods in molecular biology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsUniversity of Calgary
FundersWellcome Trust
KeywordsIn situ hybridizationBiologyMolecular biologyMessenger RNAGene expressionIn situFluorophoreXenopusFluorescence in situ hybridizationFish <Actinopterygii>RNAFluorescenceGeneGeneticsChemistryOpticsChromosome

Abstract

fetched live from OpenAlex

In situ hybridization involves the hybridization of an antisense RNA probe to an mRNA transcript and it is a powerful method for the characterization of gene expression in tissues, organs, or whole organisms. Performed as a whole mount (WISH), it allows the detection of mRNA transcripts in three dimensions, while combined with sectioning, either before or after hybridization, it provides gene expression information with cellular resolution. FISH relies on the fluorescence detection of probes and is the method of choice for the simultaneous detection of transcripts with similar or overlapping expression patterns, as each can be clearly distinguished by the selection of fluorophore. Here, we describe a protocol for performing multicolor FISH in Xenopus embryos in whole mounts and sections that can be further combined with antibody staining.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.004

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 head0.015
GPT teacher head0.353
Teacher spread0.338 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations23
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueMethods in molecular biologySame topicDevelopmental Biology and Gene RegulationFrench-language works237,207