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Record W2043856061 · doi:10.1039/b801724g

Linking the kinome and phosphorylome—a comprehensive review of approaches to find kinase targets

2008· review· en· W2043856061 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMolecular BioSystems · 2008
Typereview
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsUniversity of TorontoLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
FundersCanadian Institutes of Health ResearchNational Cancer InstituteGenome Canada
KeywordsKinomeKinasePhosphorylationBiologyComputational biologyProtein phosphorylationCell biologyProtein kinase A

Abstract

fetched live from OpenAlex

Protein phosphorylation is associated with most cell signaling and developmental processes in eukaryotes. Despite the vast extent of the phosphoproteome within the cell, connecting specific kinases with relevant targets remains a significant experimental frontier. The challenge of linking kinases and their substrates reflects the complexity of kinase function. For example, kinases tend to exert their biological effects through supernumerary, redundant phosphorylation, often on multiple protein complex components. Although these types of phosphorylation events are biologically significant, those kinases responsible are often difficult to identify. Recent methods for global analysis of protein phosphorylation promise to substantially accelerate efforts to map the dynamic phosphorylome. Here, we review both conventional methods to identify kinase targets and more comprehensive genomic and proteomic approaches to connect the kinome and phosphorylome.

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 score0.911
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.081
GPT teacher head0.302
Teacher spread0.220 · 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