AIMC Topic: Gene Editing

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CRISPR-Cas-Based Biomonitoring for Marine Environments: Toward CRISPR RNA Design Optimization Via Deep Learning.

The CRISPR journal Jul 12, 2023
Almost all of Earth's oceans are now impacted by multiple anthropogenic stressors, including the spread of nonindigenous species, harmful algal blooms, and pathogens. Early detection is critical to manage these stressors effectively and to protect ma...
Biological Monitoring Deep Learning CRISPR-Cas Systems RNA Gene Editing Artificial Intelligence Ecosystem
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Prediction of on-target and off-target activity of CRISPR-Cas13d guide RNAs using deep learning.

Nature biotechnology Jul 3, 2023
Transcriptome engineering applications in living cells with RNA-targeting CRISPR effectors depend on accurate prediction of on-target activity and off-target avoidance. Here we design and test ~200,000 RfxCas13d guide RNAs targeting essential genes i...
Deep Learning CRISPR-Cas Systems Humans Gene Editing RNA, Guide, CRISPR-Cas Systems RNA Clustered Regularly Interspaced Short Palindromic Repeats
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Deep learning models to predict the editing efficiencies and outcomes of diverse base editors.

Nature biotechnology May 15, 2023
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 ...
Deep Learning Gene Editing RNA, Guide, CRISPR-Cas Systems CRISPR-Cas Systems Alkanesulfonic Acids CRISPR-Associated Protein 9
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Enabling technology and core theory of synthetic biology.

Science China. Life sciences Feb 6, 2023
Synthetic biology provides a new paradigm for life science research ("build to learn") and opens the future journey of biotechnology ("build to use"). Here, we discuss advances of various principles and technologies in the mainstream of the enabling ...
Genome Gene Editing Biotechnology Artificial Intelligence Synthetic Biology
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Predicting prime editing efficiency and product purity by deep learning.

Nature biotechnology Jan 16, 2023
Prime editing is a versatile genome editing tool but requires experimental optimization of the prime editing guide RNA (pegRNA) to achieve high editing efficiency. Here we conducted a high-throughput screen to analyze prime editing outcomes of 92,423...
Hepatocytes Gene Editing Humans CRISPR-Cas Systems Mutation Neural Networks, Computer Deep Learning
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Predicting CRISPR/Cas9 Repair Outcomes by Attention-Based Deep Learning Framework.

Cells Jun 5, 2022
As a simple and programmable nuclease-based genome editing tool, the CRISPR/Cas9 system has been widely used in target-gene repair and gene-expression regulation. The DNA mutation generated by CRISPR/Cas9-mediated double-strand breaks determines its ...
Gene Editing Endonucleases CRISPR-Cas Systems Mutation Deep Learning
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Somatic Genome Editing with the Use of AI: Big Promises but Doubled Legal Issues.

European journal of health law Apr 8, 2022
Both Artificial Intelligence ('AI') and genome editing are technologies that on their own promise to revolutionise healthcare. But their common application can facilitate progress in the field even more. Multiplied benefits go along with increased ri...
Artificial Intelligence Delivery of Health Care Technology Health Facilities Humans Gene Editing
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Deep Learning-Assisted Automated Single Cell Electroporation Platform for Effective Genetic Manipulation of Hard-to-Transfect Cells.

Small (Weinheim an der Bergstrasse, Germany) Mar 21, 2022
Genome engineering of cells using CRISPR/Cas systems has opened new avenues for pharmacological screening and investigating the molecular mechanisms of disease. A critical step in many such studies is the intracellular delivery of the gene editing ma...
Induced Pluripotent Stem Cells Electroporation CRISPR-Cas Systems Gene Editing Humans Deep Learning
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Sequence motifs and prediction model of GBE editing outcomes based on target library analysis and machine learning.

Journal of genetics and genomics = Yi chuan xue bao Dec 2, 2021
Gene Editing Gene Library Machine Learning
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Predicting base editing outcomes with an attention-based deep learning algorithm trained on high-throughput target library screens.

Nature communications Aug 25, 2021
Base editors are chimeric ribonucleoprotein complexes consisting of a DNA-targeting CRISPR-Cas module and a single-stranded DNA deaminase. They enable transition of C•G into T•A base pairs and vice versa on genomic DNA. While base editors have great ...
High-Throughput Nucleotide Sequencing Gene Editing Base Pairing Gene Library Algorithms Deep Learning Humans Genome
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