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Record W4206612479 · doi:10.3410/f.740075071.793586178

Faculty Opinions recommendation of Genetically encoded multivalent liquid glycan array displayed on M13 bacteriophage.

2021· dataset· en· W4206612479 on OpenAlexaboutno aff
Jeff Gildersleeve

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2021
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlycosylation and Glycoproteins Research
Canadian institutionsnot available
Fundersnot available
KeywordsGlycanGlycomicsLIGAMolecular biologyComputational biologyChemistryBiologyMedicineGlycoprotein

Abstract

fetched live from OpenAlex

The central dogma of biology does not allow for the study of glycans using DNA sequencing. We report a liquid glycan array (LiGA) platform comprising a library of DNA 'barcoded' M13 virions that display 30-1,500 copies of glycans per phage. A LiGA is synthesized by acylation of the phage pVIII protein with a dibenzocyclooctyne, followed by ligation of azido-modified glycans. Pulldown of the LiGA with lectins followed by deep sequencing of the barcodes in the bound phage decodes the optimal structure and density of the recognized glycans. The LiGA is target agnostic and can measure the glycan-binding profile of lectins, such as CD22, on cells in vitro and immune cells in a live mouse. From a mixture of multivalent glycan probes, LiGAs identify the glycoconjugates with optimal avidity necessary for binding to lectins on living cells in vitro and in vivo. PMID: 33958792 Funding information This work was supported by: UAlberta | Canadian Glycomics Network (GlycoNet), Grant ID: TP-22 UAlberta | Canadian Glycomics Network (GlycoNet), Grant ID: SD-1 NIAID NIH HHS, United States Grant ID: P01 AI058113 NIAID NIH HHS, United States Grant ID: R01 AI099141 NIAID NIH HHS, United States Grant ID: R01 AI132790 NHLBI NIH HHS, United States Grant ID: P01 HL107151 More Less keyboard_arrow_down

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.490
Threshold uncertainty score0.727

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.4900.280

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 head0.026
GPT teacher head0.355
Teacher spread0.329 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

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