AIMC Topic: Gene Editing

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CRISPRpred(SEQ): a sequence-based method for sgRNA on target activity prediction using traditional machine learning.

BMC bioinformatics Jun 1, 2020
BACKGROUND: The latest works on CRISPR genome editing tools mainly employs deep learning techniques. However, deep learning models lack explainability and they are harder to reproduce. We were motivated to build an accurate genome editing tool using ...
Deep Learning ROC Curve Databases, Genetic Machine Learning Algorithms Reproducibility of Results Base Sequence Gene Editing RNA, Guide, CRISPR-Cas Systems Area Under Curve CRISPR-Cas Systems HEK293 Cells Humans
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Deep learning improves the ability of sgRNA off-target propensity prediction.

BMC bioinformatics Feb 10, 2020
BACKGROUND: CRISPR/Cas9 system, as the third-generation genome editing technology, has been widely applied in target gene repair and gene expression regulation. Selection of appropriate sgRNA can improve the on-target knockout efficacy of CRISPR/Cas9...
Humans RNA Deep Learning Gene Editing CRISPR-Cas Systems
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SpCas9 activity prediction by DeepSpCas9, a deep learning-based model with high generalization performance.

Science advances Nov 6, 2019
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...
Reproducibility of Results Deep Learning CRISPR-Cas Systems Humans Gene Editing RNA, Guide, CRISPR-Cas Systems CRISPR-Associated Protein 9 Mutation Internet
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Prediction of sgRNA on-target activity in bacteria by deep learning.

BMC bioinformatics Oct 24, 2019
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 Gene Editing Neural Networks, Computer Deep Learning RNA, Guide, CRISPR-Cas Systems Sequence Deletion
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An overview and metanalysis of machine and deep learning-based CRISPR gRNA design tools.

RNA biology Sep 27, 2019
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...
Gene Editing Gene Targeting RNA, Guide, CRISPR-Cas Systems Deep Learning CRISPR-Cas Systems Humans Machine Learning Algorithms Sensitivity and Specificity
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Optimized CRISPR guide RNA design for two high-fidelity Cas9 variants by deep learning.

Nature communications Sep 19, 2019
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...
Deep Learning Cell Line, Tumor Mice CRISPR-Cas Systems Internet HeLa Cells Humans Animals INDEL Mutation RNA, Guide, CRISPR-Cas Systems Gene Editing Promoter Regions, Genetic Endonucleases HEK293 Cells Base Sequence Clustered Regularly Interspaced Short Palindromic Repeats
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Predicting CRISPR/Cas9-Induced Mutations for Precise Genome Editing.

Trends in biotechnology Sep 13, 2019
SpCas9 creates blunt end cuts in the genome and generates random and unpredictable mutations through error-prone repair systems. However, a growing body of recent evidence points instead to Cas9-induced staggered end generation, nonrandomness of muta...
DNA End-Joining Repair Machine Learning Models, Genetic CRISPR-Cas Systems Mutation Gene Editing DNA Repair
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Unlocking HDR-mediated nucleotide editing by identifying high-efficiency target sites using machine learning.

Scientific reports Feb 26, 2019
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...
Machine Learning Oligodeoxyribonucleotides Animals DNA Repair Mutation RNA, Guide, CRISPR-Cas Systems Gene Editing DNA Breaks, Double-Stranded Mice Mice, Inbred C57BL CRISPR-Cas Systems
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Deep learning image recognition enables efficient genome editing in zebrafish by automated injections.

PloS one Jan 7, 2019
One of the most popular techniques in zebrafish research is microinjection. This is a rapid and efficient way to genetically manipulate early developing embryos, and to introduce microbes, chemical compounds, nanoparticles or tracers at larval stages...
Gene Knock-In Techniques Animals Gene Editing Deep Learning Embryo, Nonmammalian Zebrafish Microinjections Embryonic Development
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Prediction of CRISPR sgRNA Activity Using a Deep Convolutional Neural Network.

Journal of chemical information and modeling Dec 7, 2018
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...
Nucleic Acid Conformation Models, Molecular RNA, Guide, CRISPR-Cas Systems CRISPR-Cas Systems Deep Learning Gene Editing Computational Biology
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