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Record W2110783096 · doi:10.1093/bioinformatics/btq264

GPCR-OKB: the G Protein Coupled Receptor Oligomer Knowledge Base

2010· article· en· W2110783096 on OpenAlexaff
George Khelashvili, Kevin C. Dorff, Jufang Shan, Marta Camacho‐Artacho, Lucy Skrabanek, Bas Vroling, Michel Bouvier, Lakshmi A. Devi, Susan R. George, Jonathan A. Javitch, Martin J. Lohse, Graeme Milligan, Richard R. Neubig, Krzysztof Palczewski, Marc Parmentier, Jean‐Philippe Pin, Gerrit Vriend, Fabien Campagne, Marta Filizola

Bibliographic record

VenueBioinformatics · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersNational Institute on Drug AbuseNational Institute of Mental HealthNational Institutes of HealthNorwegian Biodiversity Information Centre
KeywordsOligomerG protein-coupled receptorBase (topology)ReceptorComputer scienceComputational biologyChemistryBiologyBiochemistryMathematicsPolymer chemistry

Abstract

fetched live from OpenAlex

SUMMARY: Rapid expansion of available data about G Protein Coupled Receptor (GPCR) dimers/oligomers over the past few years requires an effective system to organize this information electronically. Based on an ontology derived from a community dialog involving colleagues using experimental and computational methodologies, we developed the GPCR-Oligomerization Knowledge Base (GPCR-OKB). GPCR-OKB is a system that supports browsing and searching for GPCR oligomer data. Such data were manually derived from the literature. While focused on GPCR oligomers, GPCR-OKB is seamlessly connected to GPCRDB, facilitating the correlation of information about GPCR protomers and oligomers. AVAILABILITY AND IMPLEMENTATION: The GPCR-OKB web application is freely available at http://www.gpcr-okb.org

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.010
GPT teacher head0.233
Teacher spread0.223 · 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 teacher head, not a consensus.

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

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

Citations75
Published2010
Admission routes1
Has abstractyes

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