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Record W4214840711 · doi:10.1089/crispr.2021.0109

Increasing the Targeting Scope of CRISPR Base Editing System Beyond NGG

2022· review· en· W4214840711 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe CRISPR Journal · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsCRISPRGenome editingCas9Scope (computer science)Computational biologyBiologyPoint mutationDNAWorkflowComputer scienceBase pairGeneticsMutationGeneProgramming languageDatabase

Abstract

fetched live from OpenAlex

Genome editing provides a new therapeutic strategy to cure genetic diseases. The recently developed CRISPR-Cas9 base editing technology has shown great potential to repair the majority of pathogenic point mutations in the patient's DNA precisely. Base editor is the fusion of a Cas9 nickase with a base-modifying enzyme that can change a nucleotide on a single strand of DNA without generating double-stranded DNA breaks. However, a major limitation in applying such a system is the prerequisite of a protospacer adjacent motif sequence at the desired position relative to the target site. Progress has been made to increase the targeting scope of base editors by engineering SpCas9 protein variants, establishing systems with broadened editing windows, characterizing new SpCas9 orthologs, and developing prime editing technology. In this review, we discuss recent progress in the development of CRISPR base editing, focusing on its targeting scope, and we provide a workflow for selecting a suitable base editor based on the target nucleotide sequences.

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.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.931
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.022
GPT teacher head0.335
Teacher spread0.313 · 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