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Record W1585546584 · doi:10.1159/000092507

c-Myc, Genomic Instability and Disease

2006· review· en· W1585546584 on OpenAlexafffund
Fabien Kuttler, Sabine Mai

Bibliographic record

VenueGenome dynamics · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
FundersCanadian Institutes of Health Research
KeywordsGenome instabilityBiologyOncogeneGenomeComputational biologyCancerGeneticsGeneDNACell cycleDNA damage

Abstract

fetched live from OpenAlex

The proto-oncogene c-myc has been the subject of intensive research since its discovery. It is already known that this oncogene targets multiple pathways for the initiation and promotion of tumor formation, and that deregulation of this protein is observed in numerous cancers. However, despite the plethora of information gathered, the exact role and mechanism of action of the protein still remains enigmatic. This review focuses on the role of the c-Myc protein in the induction of genomic instability and its link with the development of cancer. We briefly describe c-Myc protein, its binding partners and downstream targets as well as its role in inducing genomic instability and the c-myc-related diseases in humans and mice with regard to genomic instability. This review emphasizes the notions that c-Myc is a multifunctional protein which also affects the stability of the whole genome and triggers the initiation of a complex network of genomic instability and therefore acts beyond the characteristics of classical transcription factors that only regulate a limited number of downstream targets. We propose that c-Myc is a structural modifier of the genome that affects the nuclear organization and an important molecule in tumor cell progression through the induction of genomic instability.

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)0.000
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.011
GPT teacher head0.257
Teacher spread0.245 · 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

Citations42
Published2006
Admission routes2
Has abstractyes

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