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Record W2160480921 · doi:10.1139/o03-048

Magnetic tweezers: a sensitive tool to study DNA and chromatin at the single-molecule level

2003· review· en· W2160480921 on OpenAlexvenueno aff
Jordanka Zlatanova, Sanford H. Leuba

Bibliographic record

VenueBiochemistry and Cell Biology · 2003
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer therapeutics and mechanisms
Canadian institutionsnot available
FundersNational Cancer Institute
KeywordsMagnetic tweezersChromatinMacromoleculeMoleculeDNABiophysicsMolecular tweezersNanotechnologyPopulationOptical tweezersChemistryBiologyPhysicsMaterials scienceBiochemistrySupramolecular chemistry

Abstract

fetched live from OpenAlex

The advent of single-molecule biology has allowed unprecedented insight into the dynamic behavior of biological macromolecules and their complexes. Unexpected properties, masked by the asynchronous behavior of myriads of molecules in bulk experiments, can be revealed; equally importantly, individual members of a molecular population often exhibit distinct features in their properties. Finally, the single-molecule approaches allow us to study the behavior of biological macromolecules under applied tension or torsion; understanding the mechanical properties of these molecules helps us understand how they function in the cell. In this review, we summarize the application of magnetic tweezers (MT) to the study of DNA behavior at the single-molecule level. MT can be conveniently used to stretch DNA and introduce controlled levels of superhelicity into the molecule and to follow to a high definition the action of different types of topoisomerases. Its potential for chromatin studies is also enormous, and we will briefly present our first chromatin results.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.712
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.033
GPT teacher head0.285
Teacher spread0.252 · 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 designBench or experimental
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

Citations64
Published2003
Admission routes1
Has abstractyes

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