ReviewNature reviews. Genetics2026
Harnessing artificial intelligence to advance CRISPR-based genome editing technologies.
Review in Nature reviews. Genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Translating functional molecular knowledge into crop-breeding success.Nature reviews. Genetics · 2026Review
- From Gene Function to Precision Intervention: CRISPR/Cas9 and Stem Cell-Based Strategies as Emerging Disease-Modifying Approaches in PMOS.Stem cell reviews and reports · 2026Review
- AI-designed OpenCRISPR-1 performs robust knockout, base editing, and prime editing in rice.The New phytologist · 2026Article
- Data-centric feedback loops for next-generation immunotherapy development.Nature biomedical engineering · 2026Review
- Adaptive model-guided protein evolution with sparse data optimizes compact eukaryotic genome editors.Nature biotechnology · 2026Article
- Environmental Risk Assessment and Confinement of Genetically Engineered Trees with an Emphasis on Vegetative Reproduction.Plants (Basel, Switzerland) · 2026Review
- Reversing cancer cell behavior using AI-guided CRISPR and quantum nanobiology: a systems-based approach to epigenetic reprogramming.Gene therapy · 2026Review
- Overcoming the challenges of genome-editing essential genes.STAR protocols · 2026Review
- Harnessing artificial intelligence in plant breeding: innovations in digital phenotyping and breeding methodologies.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- Expanding the Microbial Genomic Landscape and Biotechnological Applications of CRISPR-Cas Systems.Biology · 2026Review
- Ancestral diversity in complex disease genetics: from discovery to translation.Nature reviews. Genetics · 2026Review
- A review of flavonoids at the crossroads of plant defense: integrating biotic and abiotic stress tolerance through AI- and CRISPR/Cas-guided metabolic reprogramming.Frontiers in plant science · 2026Review
- CRISPR/Cas9 in cancer therapy: clinical translation, mechanistic strategies, and therapeutic directions.Frontiers in oncology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
CRISPR-based genome editing technologies, including nuclease-based editing, base editing and prime editing, have revolutionized biological research and modern medicine by enabling precise, programmable modification of the genome and offering new therapeutic strategies for a wide range of genetic diseases. Artificial intelligence (AI), including machine learning and deep learning models, is now further advancing the field by accelerating the optimization of gene editors for diverse targets, guiding the engineering of existing tools and supporting the discovery of novel genome-editing enzymes. In this Review, we summarize key AI methodologies underlying these advances and discuss their recent noteworthy applications to genome editing technologies. We also discuss emerging opportunities, such as AI-powered virtual cell models, which can guide genome editing through target selection or prediction of functional outcomes. Finally, we identify key directions where the integration of AI methods is poised to have a substantial impact going forward.
Indexed as
Identifiers
41254174What Socratic holds
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 Socratic graph.