ReviewACS synthetic biology2025
Engineering a New Generation of Gene Editors: Integrating Synthetic Biology and AI Innovations.
Review in ACS synthetic biology, 2025. 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.
- Miniaturized CRISPR: Ultra Compact Systems for In Vivo Delivery and Portable Diagnostics.Annals of biomedical engineering · 2026Review
- Thermostability Engineering in Therapeutic Antioxidant Enzymes: From Molecular Fundamentals to Oxidative Stress Applications.International journal of molecular sciences · 2026Review
- AI-empowered human microbiome research.Gut · 2026Review
- AI-driven big data analysis and predictive modeling of infectious disease immunity: from correlates to causal, multiscale understanding.Archives of microbiology · 2026Review
- Microbial production of xanthohumol driven by synthetic biology approaches.World journal of microbiology & biotechnology · 2026Review
- Engineering genetic elements for microbial protein expression systems: Advances, challenges, applications, and prospects.Synthetic and systems biotechnology · 2026Review
- The emerging impact of CRISPR and gene editing on global crop improvement.Transgenic research · 2026Review
- Artificial Intelligence-Assisted CRISPR Gene Editing: Current Advances, Clinical Challenges, and Future Directions in Precision Medicine.Avicenna journal of medical biotechnology · 2026Review
- Beyond GMOs: transgene-free gene-edited crops for global food security.Frontiers in plant science · 2026Review
- In silico approaches for discovering microbial antiviral defense systems.Briefings in bioinformatics · 2025Review
- Genome Editing in the Chicken: From PGC-Mediated Germline Transmission to Advanced Applications.International journal of molecular sciences · 2025Review
- Recent Advances, Challenges, and Functional Applications of Protein Chemical Modification in the Food Industry.Foods (Basel, Switzerland) · 2025Review
- Gene Therapy Techniques and Delivery Methods (Review).Sovremennye tekhnologii v meditsine · 2025Review
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-Cas technology has revolutionized biology by enabling precise DNA and RNA edits with ease. However, significant challenges remain for translating this technology into clinical applications. Traditional protein engineering methods, such as rational design, mutagenesis screens, and directed evolution, have been used to address issues like low efficacy, specificity, and high immunogenicity. These methods are labor-intensive, time-consuming, and resource-intensive and often require detailed structural knowledge. Recently, computational strategies have emerged as powerful solutions to these limitations. Using artificial intelligence (AI) and machine learning (ML), the discovery and design of novel gene-editing enzymes can be streamlined. AI/ML models predict activity, specificity, and immunogenicity while also enhancing mutagenesis screens and directed evolution. These approaches not only accelerate rational design but also create new opportunities for developing safer and more efficient genome-editing tools, which could eventually be translated into the clinic.
Indexed as
Identifiers
What 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.