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Record W2544218357 · doi:10.1139/bcb-2016-0159

The discovery and development of the CRISPR system in applications in genome manipulation

2016· review· en· W2544218357 on OpenAlexafffundvenue
Veronica Lau, James Davie

Bibliographic record

VenueBiochemistry and Cell Biology · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
FundersCancerCare Manitoba Foundation
KeywordsCRISPRCas9Genome editingBiologyComputational biologyBiomedicineFunction (biology)Genome engineeringEpigenomeGeneticsGeneDNA methylation

Abstract

fetched live from OpenAlex

The clustered regularly interspaced short palindromic repeat (CRISPR) associated 9 (Cas9) system is a microbial adaptive immune system that has been recently developed for genomic engineering. From the moment the CRISPR system was discovered in Escherichia coli, the drive to understand the mechanism prevailed, leading to rapid advancement in the knowledge and applications of the CRISPR system. With the ability to characterize and understand the function of the Cas9 endonuclease came the ability to adapt the CRISPR-Cas9 system for use in a variety of applications and disciplines ranging from agriculture to biomedicine. This review will provide a brief overview of the discovery and development of the CRISPR-Cas9 system in applications such as genome regulation and epigenome engineering, as well as the challenges faced.

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)0.001
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 score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.012
GPT teacher head0.295
Teacher spread0.283 · 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

Citations19
Published2016
Admission routes3
Has abstractyes

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