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Record W1895300367 · doi:10.1186/s12985-015-0365-6

Proteomic analysis of HIV-1 Gag interacting partners using proximity-dependent biotinylation

2015· article· en· W1895300367 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

VenueVirology Journal · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiotin and Related Studies
Canadian institutionsMcGill UniversityJewish General Hospital
FundersCanadian Institutes of Health ResearchInternational AIDS SocietyMcGill University
KeywordsBiotinylationHuman immunodeficiency virus (HIV)Group-specific antigenBiologyVirologyComputational biologyAntiretroviral therapyViral life cycleVirusCell biologyViral replicationMolecular biologyViral load

Abstract

fetched live from OpenAlex

BACKGROUND: The human immunodeficiency virus type 1 (HIV-1) Gag polyprotein is necessary and sufficient to assemble non-infectious particles. Given that HIV-1 subverts many host proteins at all stages of its life cycle, it is essential to identify these interactions as potential targets for antiretroviral therapy. FINDINGS: This work demonstrates the use of proximity-dependent biotin identification (BioID) of host proteins and complexes that are proximal to the N-terminal domains of the HIV-1 Gag polyprotein. Two of the hits identified in the BioID screen were validated by immunoprecipation and confirmed the interaction of DDX17 and RPS6 with HIV-1 Gag. CONCLUSIONS: Our results show that BioID is both a successful and complementary method to screen for nearby interacting proteins of HIV-1 Gag during the replicative cycle in different cell lines.

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)0.001
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 score0.032
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.039
GPT teacher head0.324
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