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Record W2418205348 · doi:10.1007/978-1-61779-270-0_7

Affinity-Based Assays for the Identification and Quantitative Evaluation of Noncovalent Poly(ADP-Ribose)-Binding Proteins

2011· article· en· W2418205348 on OpenAlexafffund
Jean‐Philippe Gagné, Jean-François Haince, Émilie Pic, Guy G. Poirier

Bibliographic record

VenueMethods in molecular biology · 2011
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsUniversité LavalCentre hospitalier de l'Université LavalCentre hospitalier universitaire de Québec
FundersNational Cancer InstituteCanadian Institutes of Health Research
KeywordsEffectorPoly ADP ribose polymeraseCell biologyCell signalingComputational biologyChemistrySignal transductionImmunoprecipitationRiboseProtein–protein interactionBiologyPolymeraseBiochemistryDNAEnzyme

Abstract

fetched live from OpenAlex

Poly(ADP-ribose) polymerases have been linked to several cellular functions, most of which being mediated through the dynamics of poly(ADP-ribose) (pADPr). In several pathways, pADPr is the effector molecule that regulates cellular signaling and dictates biological outcomes. pAPDr is a central molecule that is capable of promoting both cell survival through the maintenance of genome integrity and cell death that occurs by way of a signal-mediated apoptotic-like process. Thus, interactions with pADPr are extremely important in bringing about the balanced regulation that controls cell fate. Further clues regarding these functions are emerging from a growing list of proteins with which pADPr interacts. Here, we describe the current approaches for investigating noncovalent protein interactions with pADPr.

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.004

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 head0.227
GPT teacher head0.512
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 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

Citations11
Published2011
Admission routes2
Has abstractyes

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Same venueMethods in molecular biologySame topicPARP inhibition in cancer therapyFrench-language works237,207