AIMC Topic: CRISPR-Cas Systems

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Easy-Prime: a machine learning-based prime editor design tool.

Genome biology Aug 19, 2021
Prime editing is a revolutionary genome-editing technology that can make a wide range of precise edits in DNA. However, designing highly efficient prime editors (PEs) remains challenging. We develop Easy-Prime, a machine learning-based program traine...
Humans Machine Learning DNA CRISPR-Cas Systems HEK293 Cells Gene Editing RNA, Guide, CRISPR-Cas Systems
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Optimization of C-to-G base editors with sequence context preference predictable by machine learning methods.

Nature communications Aug 12, 2021
Efficient and precise base editors (BEs) for C-to-G transversion are highly desirable. However, the sequence context affecting editing outcome largely remains unclear. Here we report engineered C-to-G BEs of high efficiency and fidelity, with the seq...
Mice Escherichia coli CRISPR-Cas Systems HEK293 Cells Machine Learning Female Reproducibility of Results Animals Codon Gene Library Caenorhabditis elegans Cytidine Deaminase Uracil-DNA Glycosidase Base Sequence Gene Editing Binding Sites Humans
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Enhancing CRISPR-Cas9 gRNA efficiency prediction by data integration and deep learning.

Nature communications May 28, 2021
The design of CRISPR gRNAs requires accurate on-target efficiency predictions, which demand high-quality gRNA activity data and efficient modeling. To advance, we here report on the generation of on-target gRNA activity data for 10,592 SpCas9 gRNAs. ...
Humans Software Deep Learning Gene Editing Lentivirus Computational Biology Genetic Vectors CRISPR-Cas Systems RNA, Guide, CRISPR-Cas Systems HEK293 Cells Plasmids
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Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning.

Nature biomedical engineering Apr 15, 2021
The optimization of therapeutic antibodies is time-intensive and resource-demanding, largely because of the low-throughput screening of full-length antibodies (approximately 1 × 10 variants) expressed in mammalian cells, which typically results in fe...
Receptor, ErbB-2 Trastuzumab Antigens Hybridomas Protein Binding CRISPR-Cas Systems Amino Acid Sequence Antibody Specificity Recombinational DNA Repair Mutagenesis, Site-Directed Protein Engineering Antibody Affinity Sequence Analysis, Protein Humans Animals Deep Learning
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Machine learning based CRISPR gRNA design for therapeutic exon skipping.

PLoS computational biology Jan 8, 2021
Restoring gene function by the induced skipping of deleterious exons has been shown to be effective for treating genetic disorders. However, many of the clinically successful therapies for exon skipping are transient oligonucleotide-based treatments ...
Genetic Therapy Gene Library Exons Embryonic Stem Cells RNA, Guide, CRISPR-Cas Systems Animals Humans Mice Machine Learning CRISPR-Cas Systems Cells, Cultured Gene Editing
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sgRNACNN: identifying sgRNA on-target activity in four crops using ensembles of convolutional neural networks.

Plant molecular biology Jan 1, 2021
We proposed an ensemble convolutional neural network model to identify sgRNA high on-target activity in four crops and we used one-hot encoding and k-mers for sequence encoding. As an important component of the CRISPR/Cas9 system, single-guide RNA (s...
HEK293 Cells Sorghum Gene Editing Glycine max RNA, Guide, CRISPR-Cas Systems Internet HeLa Cells Crops, Agricultural HCT116 Cells Humans Computational Biology Neural Networks, Computer Zea mays Algorithms CRISPR-Cas Systems Triticum
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Mobile Health (mHealth) Viral Diagnostics Enabled with Adaptive Adversarial Learning.

ACS nano Nov 23, 2020
Deep-learning (DL)-based image processing has potential to revolutionize the use of smartphones in mobile health (mHealth) diagnostics of infectious diseases. However, the high variability in cellphone image data acquisition and the common need for l...
CRISPR-Cas Systems Point-of-Care Testing Signal Processing, Computer-Assisted Platinum Telemedicine Deep Learning COVID-19 Testing Image Processing, Computer-Assisted Neural Networks, Computer Disaster Planning Smartphone Antigens, Viral COVID-19 Communicable Disease Control Humans Metal Nanoparticles Reproducibility of Results Public Health
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Assessing Public Opinion on CRISPR-Cas9: Combining Crowdsourcing and Deep Learning.

Journal of medical Internet research Aug 31, 2020
BACKGROUND: The discovery of the CRISPR-Cas9-based gene editing method has opened unprecedented new potential for biological and medical engineering, sparking a growing public debate on both the potential and dangers of CRISPR applications. Given the...
CRISPR-Cas Systems Humans Public Opinion Deep Learning Crowdsourcing
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Machine-learning approach expands the repertoire of anti-CRISPR protein families.

Nature communications Jul 29, 2020
The CRISPR-Cas are adaptive bacterial and archaeal immunity systems that have been harnessed for the development of powerful genome editing and engineering tools. In the incessant host-parasite arms race, viruses evolved multiple anti-defense mechani...
Bacteriophages CRISPR-Cas Systems Viral Proteins CRISPR-Associated Protein 9 Datasets as Topic Sequence Homology, Amino Acid Host-Parasite Interactions Sequence Analysis, Protein Gene Editing Archaea Machine Learning Bacteria Computational Biology
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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 Humans RNA, Guide, CRISPR-Cas Systems CRISPR-Cas Systems ROC Curve Machine Learning Databases, Genetic Algorithms HEK293 Cells Area Under Curve Reproducibility of Results Base Sequence Gene Editing
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