AIMC Topic: RNA, Guide, CRISPR-Cas Systems

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Prime editor with rational design and AI-driven optimization for reverse editing window and enhanced fidelity.

Nature communications Jun 3, 2025
Prime editing (PE) is a precise tool for introducing genetic mutations in eukaryotes. Extending the efficient editing scope and mitigating undesired byproducts are possible. We introduce reverse PE (rPE), a SpCas9-directed variant that enabled DNA ed...
RNA, Guide, CRISPR-Cas Systems CRISPR-Associated Protein 9 Artificial Intelligence CRISPR-Cas Systems HEK293 Cells Gene Editing Humans
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CRISPR-MFH: A Lightweight Hybrid Deep Learning Framework with Multi-Feature Encoding for Improved CRISPR-Cas9 Off-Target Prediction.

Genes Mar 28, 2025
BACKGROUND: The CRISPR-Cas9 system has emerged as one of the most promising gene-editing technologies in biology. However, off-target effects remain a significant challenge. While recent advances in deep learning have led to the development of models...
Deep Learning CRISPR-Cas Systems Humans Gene Editing RNA, Guide, CRISPR-Cas Systems
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Accurate Prediction of CRISPR/Cas13a Guide Activity Using Feature Selection and Deep Learning.

Journal of chemical information and modeling Mar 17, 2025
CRISPR/Cas13a serves as a key tool for nucleic acid tests; therefore, accurate prediction of its activity is essential for creating robust and sensitive diagnosis. In this study, we create a dual-branch neural network model that achieves high predict...
Neural Networks, Computer Deep Learning RNA, Guide, CRISPR-Cas Systems CRISPR-Cas Systems
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Transitioning from wet lab to artificial intelligence: a systematic review of AI predictors in CRISPR.

Journal of translational medicine Feb 4, 2025
The revolutionary CRISPR-Cas9 system leverages a programmable guide RNA (gRNA) and Cas9 proteins to precisely cleave problematic regions within DNA sequences. This groundbreaking technology holds immense potential for the development of targeted ther...
RNA, Guide, CRISPR-Cas Systems Humans Artificial Intelligence CRISPR-Cas Systems Gene Editing
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Balanced Training Sets Improve Deep Learning-Based Prediction of CRISPR sgRNA Activity.

ACS synthetic biology Nov 4, 2024
CRISPR-Cas systems have transformed the field of synthetic biology by providing a versatile method for genome editing. The efficiency of CRISPR systems is largely dependent on the sequence of the constituent sgRNA, necessitating the development of co...
Gene Editing RNA, Guide, CRISPR-Cas Systems Clustered Regularly Interspaced Short Palindromic Repeats Neural Networks, Computer Deep Learning CRISPR-Cas Systems Yarrowia
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Effective genome editing with an enhanced ISDra2 TnpB system and deep learning-predicted ωRNAs.

Nature methods Sep 23, 2024
Transposon (IS200/IS605)-encoded TnpB proteins are predecessors of class 2 type V CRISPR effectors and have emerged as one of the most compact genome editors identified thus far. Here, we optimized the design of Deinococcus radiodurans (ISDra2) TnpB ...
Deep Learning Mice CRISPR-Cas Systems HEK293 Cells Humans RNA, Guide, CRISPR-Cas Systems Animals Gene Editing Deinococcus DNA Transposable Elements
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Machine learning prediction of prime editing efficiency across diverse chromatin contexts.

Nature biotechnology Jun 21, 2024
The success of prime editing depends on the prime editing guide RNA (pegRNA) design and target locus. Here, we developed machine learning models that reliably predict prime editing efficiency. PRIDICT2.0 assesses the performance of pegRNAs for all ed...
Humans Machine Learning Chromatin Animals RNA, Guide, CRISPR-Cas Systems Gene Editing
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CrnnCrispr: An Interpretable Deep Learning Method for CRISPR/Cas9 sgRNA On-Target Activity Prediction.

International journal of molecular sciences Apr 17, 2024
CRISPR/Cas9 is a powerful genome-editing tool in biology, but its wide applications are challenged by a lack of knowledge governing single-guide RNA (sgRNA) activity. Several deep-learning-based methods have been developed for the prediction of on-ta...
RNA, Guide, CRISPR-Cas Systems Humans CRISPR-Cas Systems Gene Editing Neural Networks, Computer Deep Learning
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CRISPR-M: Predicting sgRNA off-target effect using a multi-view deep learning network.

PLoS computational biology Mar 14, 2024
Using the CRISPR-Cas9 system to perform base substitutions at the target site is a typical technique for genome editing with the potential for applications in gene therapy and agricultural productivity. When the CRISPR-Cas9 system uses guide RNA to d...
RNA, Guide, CRISPR-Cas Systems CRISPR-Cas Systems Neural Networks, Computer Gene Editing Deep Learning
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Interpretable neural architecture search and transfer learning for understanding CRISPR-Cas9 off-target enzymatic reactions.

Nature computational science Dec 14, 2023
Finely tuned enzymatic pathways control cellular processes, and their dysregulation can lead to disease. Developing predictive and interpretable models for these pathways is challenging because of the complexity of the pathways and of the cellular an...
CRISPR-Cas Systems Machine Learning Neural Networks, Computer RNA, Guide, CRISPR-Cas Systems Genomics
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