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Enregistrement W2057498926 · doi:10.1074/mcp.m900517-mcp200

Establishment of a Protein Frequency Library and Its Application in the Reliable Identification of Specific Protein Interaction Partners

2009· article· en· W2057498926 sur OpenAlexaff
Séverine Boulon, Yasmeen Ahmad, Laura Trinkle‐Mulcahy, Céline Verheggen, Peter Gregor, Édouard Bertrand, Mark Whitehorn, Angus I. Lamond

Notice bibliographique

RevueMolecular & Cellular Proteomics · 2009
Typearticle
Langueen
DomaineChemistry
ThématiqueAdvanced Proteomics Techniques and Applications
Établissements canadiensUniversity of Ottawa
Organismes subventionnairesBiotechnology and Biological Sciences Research CouncilWellcome Trust
Mots-clésIdentification (biology)Computational biologyComputer scienceBiology

Résumé

récupéré en direct d'OpenAlex

The reliable identification of protein interaction partners and how such interactions change in response to physiological or pathological perturbations is a key goal in most areas of cell biology. Stable isotope labeling with amino in cell to a protein and how with to and protein and to protein is a protein of The of in and in a and and and to and in The is a to a to The of to is in or of protein The reliable identification of protein interaction partners and how such interactions change in response to physiological or pathological perturbations is a key goal in most areas of cell biology. Stable isotope labeling with amino in cell to a protein and how with to and protein and to protein is a protein of The of in and in a and and and to and in The is a to a to The of to is in or of protein and of and protein and with or interaction to and and of a The of a in of protein of protein interactions physiological to a to a a key goal in cell protein interaction partners and of protein and how interactions and and interactions in response to or with a of in of or protein in of interaction partners protein to The most and to or of protein of of in and to The of with a and protein and of protein in of protein in and to interaction or a of protein in identification of a of and of cell of protein in of of in of to in protein interaction or and of in to protein or of or to of and a a of protein interaction and protein in and protein protein and of protein and protein interaction to and to of interaction with interaction or in protein or of interaction interaction of protein 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Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,031
Score d'incertitude au seuil0,675

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,009
Tête enseignante GPT0,247
Écart entre enseignants0,238 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations68
Publié2009
Routes d'admission1
Résumé présentoui

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