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Record W3197824028 · doi:10.1002/cbic.202100327

What is the Sugar Code?

2021· review· en· W3197824028 on OpenAlexaff
Hans‐Joachim Gabius, Mare Čudić, Tammo Diercks, Herbert Kaltner, Jürgen Kopitz, Kevin H. Mayo, Paul V. Murphy, Stefan Oscarson, René Roy, Andreas Schedlbauer, Stefan Toegel, Antonio Romero

Bibliographic record

VenueChemBioChem · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlycosylation and Glycoproteins Research
Canadian institutionsUniversité du Québec à Montréal
FundersNational Cancer InstituteNational Institutes of HealthMinisterio de Asuntos Económicos y Transformación Digital, Gobierno de EspañaScience Foundation Ireland
KeywordsGlycanGlycosidic bondBiochemistryContext (archaeology)Computational biologyGenetic codeChemistryNucleic acidDNABiologyGlycoproteinEnzyme

Abstract

fetched live from OpenAlex

A code is defined by the nature of the symbols, which are used to generate information-storing combinations (e. g. oligo- and polymers). Like nucleic acids and proteins, oligo- and polysaccharides are ubiquitous, and they are a biochemical platform for establishing molecular messages. Of note, the letters of the sugar code system (third alphabet of life) excel in coding capacity by making an unsurpassed versatility for isomer (code word) formation possible by variability in anomery and linkage position of the glycosidic bond, ring size and branching. The enzymatic machinery for glycan biosynthesis (writers) realizes this enormous potential for building a large vocabulary. It includes possibilities for dynamic editing/erasing as known from nucleic acids and proteins. Matching the glycome diversity, a large panel of sugar receptors (lectins) has developed based on more than a dozen folds. Lectins 'read' the glycan-encoded information. Hydrogen/coordination bonding and ionic pairing together with stacking and C-H/π-interactions as well as modes of spatial glycan presentation underlie the selectivity and specificity of glycan-lectin recognition. Modular design of lectins together with glycan display and the nature of the cognate glycoconjugate account for the large number of post-binding events. They give an entry to the glycan vocabulary its functional, often context-dependent meaning(s), hereby building the dictionary of the sugar code.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.004

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 head0.051
GPT teacher head0.367
Teacher spread0.317 · 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 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

Citations44
Published2021
Admission routes1
Has abstractyes

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