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Record W2996551274

G-quadruplex dynamics Proteins and proteomics

2017· article· en· W2996551274 on OpenAlexaboutno aff
Robert W. Harkness, Anthony Mittermaier

Bibliographic record

VenueBiochimica et Biophysica Acta · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsnot available
Fundersnot available
KeywordsNucleic acidGuanosineComputational biologyFunction (biology)G-quadruplexBiophysicsDynamics (music)ChemistryMolecular dynamicsProteomicsDNABiologyGeneCell biologyPhysicsBiochemistryComputational chemistry
DOInot available

Abstract

fetched live from OpenAlex

G-quadruplexes (GQs) are four-stranded nucleic acid secondary structures formed by guanosine (G)-rich DNA and RNA sequences. It is becoming increasingly clear that cellular processes including gene expression and mRNA translation are regulated by GQs. GQ structures have been extensively characterized, however little attention to date has been paid to their conformational dynamics, despite the fact that many biological GQ sequences populate multiple structures of similar free energies, leading to an ensemble of exchanging conformations. The impact of these dynamics on biological function is currently not well understood. Recently, structural dynamics have been demonstrated to entropically stabilize GQ ensembles, potentially modulating gene expression. Transient, low-populated states in GQ ensembles may additionally regulate nucleic acid interactions and function. This review will underscore the interplay of GQ dynamics and biological function, focusing on several dynamic processes for biological GQs and the characterization of GQ dynamics by nuclear magnetic resonance (NMR) spectroscopy in conjunction with other biophysical techniques. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.

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)0.000
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 score0.008
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
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 head0.008
GPT teacher head0.255
Teacher spread0.246 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations1
Published2017
Admission routes1
Has abstractyes

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