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Record W2463154522 · doi:10.1021/acsinfecdis.6b00084

Chemical Methods for Probing Virus–Host Proteomic Interactions

2016· review· en· W2463154522 on OpenAlexafffund
Miroslava Strmiskova, Geneviève F. Desrochers, Tyler A. Shaw, Megan H. Powdrill, Matthew A. Lafrenière, John Paul Pezacki

Bibliographic record

VenueACS Infectious Diseases · 2016
Typereview
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaInstitute of Infection and ImmunityFonds de recherche du Québec – Nature et technologiesCanadian Institutes of Health Research
KeywordsHost (biology)InfectivityBiologyComputational biologyVirusMechanism (biology)Host factorsVirologyGenetics

Abstract

fetched live from OpenAlex

Interactions between host and pathogen proteins constitute an important aspect of both infectivity and the host immune response. Different viruses have evolved complex mechanisms to hijack host-cell machinery and metabolic pathways to redirect resources and energy flow toward viral propagation. These interactions are often critical to the virus, and thus understanding these interactions at a molecular level gives rise to opportunities to develop novel antiviral strategies for therapeutic intervention. This review summarizes current advances in chemoproteomic methods for studying these molecular altercations between different viruses and their hosts.

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 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)0.004
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 score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.084
GPT teacher head0.491
Teacher spread0.406 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2016
Admission routes2
Has abstractyes

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