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Systematic Mapping of Genetic Interaction Networks

2008· review· en· W2138470019 on OpenAlexafffund
Scott J. Dixon, Michael Costanzo, Anastasia Baryshnikova, Brenda Andrews, Charles Boone

Bibliographic record

VenueAnnual Review of Genetics · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGene Regulatory Network Analysis
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchGenome Canada
KeywordsBiologyGenetic screenSchizosaccharomyces pombeModel organismDrosophila melanogasterCaenorhabditis elegansGeneticsComputational biologySaccharomyces cerevisiaePhenotypeYeastSchizosaccharomycesSystems biologySaccharomycesGene

Abstract

fetched live from OpenAlex

Genetic interactions influencing a phenotype of interest can be identified systematically using libraries of genetic tools that perturb biological systems in a defined manner. Systematic screens conducted in the yeast Saccharomyces cerevisiae have identified thousands of genetic interactions and provided insight into the global structure of biological networks. Techniques enabling systematic genetic interaction mapping have been extended to other single-celled organisms, the bacteria Escherichia coli and the yeast Schizosaccharomyces pombe, opening the way to comparative investigations of interaction networks. Genetic interaction screens in Caenorhabditis elegans, Drosophila melanogaster, and mammalian models are helping to improve our understanding of metazoan-specific signaling pathways. Together, our emerging knowledge of the genetic wiring diagrams of eukaryotic and prokaryotic cells is providing a new understanding of the relationship between genotype and phenotype.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0000.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.018
GPT teacher head0.303
Teacher spread0.285 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations302
Published2008
Admission routes2
Has abstractyes

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