Applications of Alternative Nucleases in the Age of CRISPR/Cas9
Bibliographic record
Abstract
Breakthroughs in the development of programmable site-specific nucleases, including zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), meganucleases (MNs), and most recently, the clustered regularly interspaced short palindromic repeats (CRISPR) associated proteins (including Cas9) have greatly enabled and accelerated genome editing. By targeting double-strand breaks to user-defined locations, the rates of DNA repair events are greatly enhanced relative to un-catalyzed events at the same sites. However, the underlying biology of each genome-editing nuclease influences the targeting potential, the spectrum of off-target cleavages, the ease-of-use, and the types of recombination events at targeted double-strand breaks. No single genome-editing nuclease is optimized for all possible applications. Here, we focus on the diversity of nuclease domains available for genome editing, highlighting biochemical properties and the potential applications that are best suited to each domain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".