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Record W2009713171 · doi:10.4161/psb.3.12.6848

Comprehensive analysis of protein-protein interactions between Arabidopsis MAPKs and MAPK kinases helps define potential MAPK signalling modules

2008· article· en· W2009713171 on OpenAlexaff
Jin‐Suk Lee, Kyung Won Huh, Apurva Bhargava, Brian E. Ellis

Bibliographic record

VenuePlant Signaling & Behavior · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsCanada's Michael Smith Genome Sciences CentreMichael Smith Health Research BCUniversity of British Columbia
Fundersnot available
KeywordsArabidopsisBiologyKinaseMAPK/ERK pathwayCell biologyProtein kinase AMitogen-activated protein kinaseSignallingGeneComputational biologyGeneticsMutant

Abstract

fetched live from OpenAlex

The Arabidopsis genome encodes a 20-member gene family of mitogen-activated protein kinases (MPKs) but biological roles have only been identified for a small subset of these crucial signalling components. In particular, it is unclear how the MPKs may be organized into functional modules within the cell. To gain insight into their potential relationships, we used the yeast two-hybrid system to conduct a directed protein-protein interaction screen between all the Arabidopsis MPKs and their upstream activators (MAPK kinases; MKK). Novel interactions were also tested in vitro for enzyme-substrate functionality, using recombinant proteins. The resulting data confirm a number of earlier reported MKK-MPK relationships, but also reveal a more extensive pattern of interactions that should help to guide future analyses of MAPK signalling in plants.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.048
GPT teacher head0.244
Teacher spread0.196 · 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
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

Citations89
Published2008
Admission routes1
Has abstractyes

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