CRISPR-Cas Systems

High-Throughput and Integrated CRISPR/Cas12a-Based Molecular Diagnosis Using a Deep Learning Enabled Microfluidic System.

ACS nano 39173188

CRISPR/Cas-based molecular diagnosis demonstrates potent potential for sensitive and rapid pathogen detection, notably in SARS-CoV-2 diagnosis and mutation tracking. Yet, a major hurdle hindering widespread practical use is its restricted throughput,...

COVID-19 CRISPR-Cas Systems Deep Learning Humans Lab-On-A-Chip Devices Microfluidic Analytical Techniques Molecular Diagnostic Techniques Mutation Nucleic Acid Amplification Techniques SARS-CoV-2

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Effective genome editing with an enhanced ISDra2 TnpB system and deep learning-predicted ωRNAs.

Nature methods 39313558

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 ...

Animals CRISPR-Cas Systems Deep Learning Deinococcus DNA Transposable Elements Gene Editing HEK293 Cells Humans Mice RNA, Guide, CRISPR-Cas Systems

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The transformative potential of AI-driven CRISPR-Cas9 genome editing to enhance CAR T-cell therapy.

Computers in biology and medicine 39260044

This narrative review examines the promising potential of integrating artificial intelligence (AI) with CRISPR-Cas9 genome editing to advance CAR T-cell therapy. AI algorithms offer unparalleled precision in identifying genetic targets, essential for...

Artificial Intelligence CRISPR-Cas Systems Gene Editing Humans Immunotherapy, Adoptive Neoplasms Receptors, Chimeric Antigen

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Deciphering Cas9 specificity: Role of domain dynamics and RNA:DNA hybrid interactions revealed through machine learning and accelerated molecular simulations.

International journal of biological macromolecules 39566771

CRISPR/Cas9 technology is widely used for gene editing, but off-targeting still remains a major concern in therapeutic applications. Although Cas9 variants with better mismatch discrimination have been developed, they have significantly lower rates o...

Bacterial Proteins CRISPR-Associated Protein 9 CRISPR-Cas Systems DNA Francisella Machine Learning Molecular Dynamics Simulation Protein Domains RNA Substrate Specificity

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Balanced Training Sets Improve Deep Learning-Based Prediction of CRISPR sgRNA Activity.

ACS synthetic biology 39495623

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...

Clustered Regularly Interspaced Short Palindromic Repeats CRISPR-Cas Systems Deep Learning Gene Editing Neural Networks, Computer RNA, Guide, CRISPR-Cas Systems Yarrowia

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Machine Learning-Assisted, Dual-Channel CRISPR/Cas12a Biosensor-In-Microdroplet for Amplification-Free Nucleic Acid Detection for Food Authenticity Testing.

ACS nano 39620398

The development of novel detection technology for meat species authenticity is imperative. Here, we developed a machine learning-supported, dual-channel biosensor-in-microdroplet platform for meat species authenticity detection named CC-drop (RISPR/C...

Animals Bacterial Proteins Biosensing Techniques CRISPR-Associated Proteins CRISPR-Cas Systems Endodeoxyribonucleases Food Analysis Machine Learning Meat Nucleic Acids

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Understanding TCR T cell knockout behavior using interpretable machine learning.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing 39670384

Genetic perturbation of T cell receptor (TCR) T cells is a promising method to unlock better TCR T cell performance to create more powerful cancer immunotherapies, but understanding the changes to T cell behavior induced by genetic perturbations rema...

Computational Biology CRISPR-Cas Systems Gene Knockout Techniques Humans Machine Learning Neoplasms Neural Networks, Computer Receptors, Antigen, T-Cell T-Lymphocytes

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High throughput variant libraries and machine learning yield design rules for retron gene editors.

Nucleic acids research 39658047

The bacterial retron reverse transcriptase system has served as an intracellular factory for single-stranded DNA in many biotechnological applications. In these technologies, a natural retron non-coding RNA (ncRNA) is modified to encode a template fo...

CRISPR-Cas Systems Gene Editing Gene Library Machine Learning RNA, Guide, CRISPR-Cas Systems RNA, Untranslated Saccharomyces cerevisiae

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DeepMEns: an ensemble model for predicting sgRNA on-target activity based on multiple features.

Briefings in functional genomics 39528429

The CRISPR/Cas9 system developed from Streptococcus pyogenes (SpCas9) has high potential in gene editing. However, its successful application is hindered by the considerable variability in target efficiencies across different single guide RNAs (sgRNA...

CRISPR-Cas Systems Deep Learning Gene Editing Neural Networks, Computer RNA, Guide, CRISPR-Cas Systems Streptococcus pyogenes

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The Evolution of Nucleic Acid-Based Diagnosis Methods from the (pre-)CRISPR to CRISPR era and the Associated Machine/Deep Learning Approaches in Relevant RNA Design.

Methods in molecular biology (Clifton, N.J.) 39312149

Nucleic acid tests (NATs) are considered as gold standard in molecular diagnosis. To meet the demand for onsite, point-of-care, specific and sensitive, trace and genotype detection of pathogens and pathogenic variants, various types of NATs have been...

Clustered Regularly Interspaced Short Palindromic Repeats CRISPR-Cas Systems Deep Learning Humans Machine Learning Molecular Diagnostic Techniques Nucleic Acid Amplification Techniques RNA

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Explore the latest research on artificial intelligence and machine learning in medicine.

High-Throughput and Integrated CRISPR/Cas12a-Based Molecular Diagnosis Using a Deep Learning Enabled Microfluidic System.

Effective genome editing with an enhanced ISDra2 TnpB system and deep learning-predicted ωRNAs.

The transformative potential of AI-driven CRISPR-Cas9 genome editing to enhance CAR T-cell therapy.

Deciphering Cas9 specificity: Role of domain dynamics and RNA:DNA hybrid interactions revealed through machine learning and accelerated molecular simulations.

Balanced Training Sets Improve Deep Learning-Based Prediction of CRISPR sgRNA Activity.

Machine Learning-Assisted, Dual-Channel CRISPR/Cas12a Biosensor-In-Microdroplet for Amplification-Free Nucleic Acid Detection for Food Authenticity Testing.

Understanding TCR T cell knockout behavior using interpretable machine learning.

High throughput variant libraries and machine learning yield design rules for retron gene editors.

DeepMEns: an ensemble model for predicting sgRNA on-target activity based on multiple features.

The Evolution of Nucleic Acid-Based Diagnosis Methods from the (pre-)CRISPR to CRISPR era and the Associated Machine/Deep Learning Approaches in Relevant RNA Design.

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