ArticleNature biotechnology2024
Deep learning models to predict the editing efficiencies and outcomes of diverse base editors.
Article in Nature biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
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Who cites it
49 citing papers in PubMed, 59 citations in OpenAlex.
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- On-target and off-target activities of CRISPR therapeutics across scales.Trends in biotechnology · 2026Review
- High-throughput evaluation of in vitro CRISPR activities enables optimized large-scale multiplex enrichment of rare variants.Nature biomedical engineering · 2026Article
- The Use of Deep Learning in RNA Therapeutic Development.ACS nano · 2026Review
- Base Editors for Engineering Industrial Microorganisms: Types, Applications, and Future Perspectives.Biotechnology journal · 2026Review
- Treatment of a severe vascular disease using a bespoke CRISPR-Cas9 base editor in mice.Nature biomedical engineering · 2026Article
- Bibliometric-Based Analysis of Global Trends and Collaborative Networks in Plant Genetic Engineering (1994-2024).Plant biotechnology journal · 2026Review
- Disordered protein LAT encodes relative levels of signaling pathways in T cell activation.Science (New York, N.Y.) · 2026Article
- Engineering Compact Base Editors by AlphaFold-Guided Mutation Scan and Escherichia coli-Based Tri-Selection.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- High-precision cytosine base editors by evolving nucleic-acid-recognition hotspots in deaminase.Nature biotechnology · 2026Article
- Quantum inspired feature engineering for explainable EEG signal classification.Scientific reports · 2026Article
- Harnessing artificial intelligence to advance CRISPR-based genome editing technologies.Nature reviews. Genetics · 2026Review
- GenomePAM directs PAM characterization and engineering of CRISPR-Cas nucleases using mammalian genome repeats.Nature biomedical engineering · 2026Article
- Computation and deep-learning-driven advances in CRISPR genome editing.Nature structural & molecular biology · 2026Review
- A Global Assessment of the Transcription-Dependent Single Nucleotide Variants Relies on the Characteristics of RNA-Sequencing Technologies.Biomolecules · 2026Article
- Feature representation for explainable CRISPR off-target prediction and base editing efficiency.Frontiers in bioinformatics · 2026Article
- Deep learning models simultaneously trained on multiple datasets improve base-editing activity prediction.Nature communications · 2025Article
- A functional map of CDK-drug interactions at single amino acid resolution.bioRxiv : the preprint server for biology · 2025Article
- CRISPR-GATE: a one-stop repository and guide to computational resources for genome editing experimentation.Briefings in bioinformatics · 2025Review
- Intravitreal adenine base editing of RS1 improves vision in a preclinical mouse model of retinoschisis.Molecular therapy : the journal of the American Society of Gene Therapy · 2025Article
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
Abstract
Applications of base editing are frequently restricted by the requirement for a protospacer adjacent motif (PAM), and selecting the optimal base editor (BE) and single-guide RNA pair (sgRNA) for a given target can be difficult. To select for BEs and sgRNAs without extensive experimental work, we systematically compared the editing windows, outcomes and preferred motifs for seven BEs, including two cytosine BEs, two adenine BEs and three C•G to G•C BEs at thousands of target sequences. We also evaluated nine Cas9 variants that recognize different PAM sequences and developed a deep learning model, DeepCas9variants, for predicting which variants function most efficiently at sites with a given target sequence. We then develop a computational model, DeepBE, that predicts editing efficiencies and outcomes of 63 BEs that were generated by incorporating nine Cas9 variants as nickase domains into the seven BE variants. The predicted median efficiencies of BEs with DeepBE-based design were 2.9- to 20-fold higher than those of rationally designed SpCas9-containing BEs.
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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.