A Unified Resource for Tracking Anti-CRISPR Names
Bibliographic record
Abstract
In the battle between CRISPR-Cas* prokaryotic immune systems and the elements that they target, a diverse array of ''anti-CRISPR'' proteins have evolved.These proteins appear to have arisen independently multiple times in evolution and function through diverse mechanisms to inhibit CRISPR-Cas immunity.For comprehensive reviews on anti-CRISPRs, we direct readers to recent publications.1,2 Due to the increasing interest in anti-CRISPRs, many new families of these proteins have been discovered in the past year or so.There are now 36 distinct families of anti-CRISPRs described in the literature that block seven subtypes of CRISPR-Cas systems.[3][4][5][6][7][8][9][10][11][12] In 2015, a naming system for anti-CRISPR genes and proteins was introduced.6,13 To date, this system has been followed in all subsequent publications describing newly discovered anti-CRISPRs.However, as the rate of anti-CRISPR discovery will likely accelerate in the coming years, we feel that it would be advantageous to establish a database for the registration and tracking of anti-CRISPR names.The primary goal of this database will be to prevent redundant names being used in publications, thus avoiding confusion in the literature.Anti-CRISPR proteins are named according to the subtype they inhibit and the order in which they were discovered-for example, AcrIF1 was the first anti-CRISPR protein identified to inhibit the type I-F system.The database (a Google document) can be found here: https://tinyurl.com/anti-CRISPRWe propose that this document be updated when researchers have had a manuscript accepted for publication in which new anti-CRISPRs are described.We suggest that the authors upload relevant data to the spreadsheet, including the name, CRISPR-Cas subtype inhibited, reference, and amino-acid sequence of the anti-CRISPR (Table 1).This spreadsheet may also be utilized by those preparing a manuscript for submission to ensure that they use anti-CRISPR names that are still available.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.012 | 0.016 |
| Insufficient payload (model declined to judge) | 0.045 | 0.051 |
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 source (direct Gemma or distilled Codex), 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".