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RNA, Guide, CRISPR-Cas Systems

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A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action.

PLoS computational biology 29036168
The adaptation of the CRISPR-Cas9 system as a genome editing technique has generated much excitement in recent years owing to its ability to manipulate targeted genes and genomic regions that are complementary to a programmed single guide RNA (sgRNA)...
Algorithms Computational Biology CRISPR-Cas Systems Gene Editing Humans Machine Learning RNA, Guide, CRISPR-Cas Systems ROC Curve
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Prediction of CRISPR sgRNA Activity Using a Deep Convolutional Neural Network.

Journal of chemical information and modeling 30485088
The CRISPR-Cas9 system derived from adaptive immunity in bacteria and archaea has been developed into a powerful tool for genome engineering with wide-ranging applications. Optimizing single-guide RNA (sgRNA) design to improve efficiency of target cl...
Computational Biology CRISPR-Cas Systems Deep Learning Gene Editing Models, Molecular Nucleic Acid Conformation RNA, Guide, CRISPR-Cas Systems
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Unlocking HDR-mediated nucleotide editing by identifying high-efficiency target sites using machine learning.

Scientific reports 30808944
Editing individual nucleotides is a crucial component for validating genomic disease association. It is currently hampered by CRISPR-Cas-mediated "base editing" being limited to certain nucleotide changes, and only achievable within a small window ar...
Animals CRISPR-Cas Systems DNA Breaks, Double-Stranded DNA Repair Gene Editing Machine Learning Mice Mice, Inbred C57BL Mutation Oligodeoxyribonucleotides RNA, Guide, CRISPR-Cas Systems
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Prediction of activity and specificity of CRISPR-Cpf1 using convolutional deep learning neural networks.

BMC bioinformatics 31195957
BACKGROUND: CRISPR-Cpf1 has recently been reported as another RNA-guided endonuclease of class 2 CRISPR-Cas system, which expands the molecular biology toolkit for genome editing. However, most of the online tools and applications to date have been d...
Algorithms Base Sequence CRISPR-Cas Systems Deep Learning Endonucleases Neural Networks, Computer RNA, Guide, CRISPR-Cas Systems
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Optimized CRISPR guide RNA design for two high-fidelity Cas9 variants by deep learning.

Nature communications 31537810
Highly specific Cas9 nucleases derived from SpCas9 are valuable tools for genome editing, but their wide applications are hampered by a lack of knowledge governing guide RNA (gRNA) activity. Here, we perform a genome-scale screen to measure gRNA acti...
Animals Base Sequence Cell Line, Tumor Clustered Regularly Interspaced Short Palindromic Repeats CRISPR-Cas Systems Deep Learning Endonucleases Gene Editing HEK293 Cells HeLa Cells Humans INDEL Mutation Internet Mice Promoter Regions, Genetic RNA, Guide, CRISPR-Cas Systems
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An overview and metanalysis of machine and deep learning-based CRISPR gRNA design tools.

RNA biology 31533522
The CRISPR-Cas9 system has become the most promising and versatile tool for genetic manipulation applications. Albeit the technology has been broadly adopted by both academic and pharmaceutic societies, the activity (on-target) and specificity (off-t...
Algorithms CRISPR-Cas Systems Deep Learning Gene Editing Gene Targeting Humans Machine Learning RNA, Guide, CRISPR-Cas Systems Sensitivity and Specificity
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Prediction of sgRNA on-target activity in bacteria by deep learning.

BMC bioinformatics 31651233
BACKGROUND: One of the main challenges for the CRISPR-Cas9 system is selecting optimal single-guide RNAs (sgRNAs). Recently, deep learning has enhanced sgRNA prediction in eukaryotes. However, the prokaryotic chromatin structure is different from euk...
Bacteria CRISPR-Cas Systems Deep Learning Gene Editing Neural Networks, Computer RNA, Guide, CRISPR-Cas Systems Sequence Deletion
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SpCas9 activity prediction by DeepSpCas9, a deep learning-based model with high generalization performance.

Science advances 31723604
We evaluated SpCas9 activities at 12,832 target sequences using a high-throughput approach based on a human cell library containing single-guide RNA-encoding and target sequence pairs. Deep learning-based training on this large dataset of SpCas9-indu...
CRISPR-Associated Protein 9 CRISPR-Cas Systems Deep Learning Gene Editing Humans Internet Mutation Reproducibility of Results RNA, Guide, CRISPR-Cas Systems
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GNL-Scorer: a generalized model for predicting CRISPR on-target activity by machine learning and featurization.

Journal of molecular cell biology 31900489
Bayes Theorem CRISPR-Cas Systems Humans Machine Learning Models, Genetic Regression Analysis RNA, Guide, CRISPR-Cas Systems Software
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