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Record W2033758148 · doi:10.1139/o03-044

HMGA proteins: flexibility finds a nuclear niche?

2003· review· en· W2033758148 on OpenAlexvenueno aff
Raymond Reeves

Bibliographic record

VenueBiochemistry and Cell Biology · 2003
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Chromatin Dynamics
Canadian institutionsnot available
FundersWashington State University
KeywordsChromatinBiologyNuclear proteinCell biologyDNADNA replicationDNA-binding proteinTranscription factorTranscription (linguistics)Computational biologyGeneticsGene

Abstract

fetched live from OpenAlex

The mammalian HMGA family of chromatin proteins possesses an unusual constellation of physical, biochemical, and biological characteristics that distinguish them from other nuclear proteins. Principal among these is the fact that, unlike other proteins, they possess little detectable secondary structure prior to interactions with other macromolecules (DNA, RNA, proteins). Upon binding to substrates, however, the HMGA proteins undergo specific disordered-to-ordered structural transitions and also induce alterations in the structure of the substrates themselves. Their intrinsic structural flexibility, combined with other features such as the control of their substrate interactions via complex patterns of in vivo biochemical modifications, allows the HMGA proteins to actively participate in a wide variety of nuclear activities including DNA replication, DNA repair, chromatin remodeling, control of gene transcription, and regulation of mRNA processing

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.000
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 head0.015
GPT teacher head0.263
Teacher spread0.247 · 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

Citations43
Published2003
Admission routes1
Has abstractyes

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