ArticleGigaScience2020
CRISPRcasIdentifier: Machine learning for accurate identification and classification of CRISPR-Cas systems.
Article in GigaScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.
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Who cites it
35 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Transitioning from wet lab to artificial intelligence: a systematic review of AI predictors in CRISPR.Journal of translational medicine · 2025Pooled it
- In silico genomic analysis of resistome, virulome, and mobilome of β-lactamase-producing Klebsiella pneumoniae.Scientific reports · 2026Article
- Unveiling the biodiversity of large DNA viruses in intertidal mudflats via metagenomics.Nature communications · 2026Article
- GenomePAM directs PAM characterization and engineering of CRISPR-Cas nucleases using mammalian genome repeats.Nature biomedical engineering · 2026Article
- The complexity of multiple CRISPR arrays in strains with (co-occurring) CRISPR systems.microLife · 2026Article
- Comparative genomic analyses provide new insights into phylogenetic and functional diversification in genusFrontiers in microbiology · 2026Article
- Comprehensive analysis of CRISPR array repeat mutations reveals subtype-specific patterns and links to spacer dynamics.microLife · 2026Article
- In silico approaches for discovering microbial antiviral defense systems.Briefings in bioinformatics · 2025Review
- Application of Gene Editing Technology Based on Targeted Delivery Materials in TNBC.ACS omega · 2025Review
- CRISPR-GATE: a one-stop repository and guide to computational resources for genome editing experimentation.Briefings in bioinformatics · 2025Review
- GenomePAM directs PAM characterization and engineering of CRISPR-Cas nucleases using mammalian genome repeats.Research square · 2025Article
- Genomic landscape of nosocomial Acinetobacter baumannii: A comprehensive analysis of the resistome, virulome, and mobilome.Scientific reports · 2025Article
- A new strategy for Cas protein recognition based on graph neural networks and SMILES encoding.Scientific reports · 2025Article
- Disparate mechanisms counteract extraneous CRISPR RNA production in type II-C CRISPR-Cas systems.microLife · 2025Article
- Article
- Unlocking the potential of CRISPR tools and databases for precision genome editing.Frontiers in plant science · 2025Review
- SpacerPlacer: ancestral reconstruction of CRISPR arrays reveals the evolutionary dynamics of spacer deletions.Nucleic acids research · 2024Article
- Characterization of CRISPR-Cas Systems inPathogens (Basel, Switzerland) · 2024Article
- Identification of Family-Specific Features in Cas9 and Cas12 Proteins: A Machine Learning Approach Using Complete Protein Feature Spectrum.bioRxiv : the preprint server for biology · 2024Article
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCRISPR-Cas genes are extraordinarily diverse and evolve rapidly when compared to other prokaryotic genes. With the rapid increase in newly sequenced archaeal and bacterial genomes, manual identification of CRISPR-Cas systems is no longer viable. Thus, an automated approach is required for advancing our understanding of the evolution and diversity of these systems and for finding new candidates for genome engineering in eukaryotic models.
resultsWe introduce CRISPRcasIdentifier, a new machine learning-based tool that combines regression and classification models for the prediction of potentially missing proteins in instances of CRISPR-Cas systems and the prediction of their respective subtypes. In contrast to other available tools, CRISPRcasIdentifier can both detect cas genes and extract potential association rules that reveal functional modules for CRISPR-Cas systems. In our experimental benchmark on the most recently published and comprehensive CRISPR-Cas system dataset, CRISPRcasIdentifier was compared with recent and state-of-the-art tools. According to the experimental results, CRISPRcasIdentifier presented the best Cas protein identification and subtype classification performance.
conclusionsOverall, our tool greatly extends the classification of CRISPR cassettes and, for the first time, predicts missing Cas proteins and association rules between Cas proteins. Additionally, we investigated the properties of CRISPR subtypes. The proposed tool relies not only on the knowledge of manual CRISPR annotation but also on models trained using machine learning.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.