AIMC Topic: Genetic Vectors

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Prediction of Adeno-Associated Virus Fitness with a Protein Language-Based Machine Learning Model.

Human gene therapy
Adeno-associated virus (AAV)-based therapeutics have the potential to transform the lives of patients by delivering one-time treatments for a variety of diseases. However, a critical challenge to their widespread adoption and distribution is the high...

Advances in AAV capsid engineering: Integrating rational design, directed evolution and machine learning.

Molecular therapy : the journal of the American Society of Gene Therapy
Adeno-associated virus (AAV) has emerged as a highly promising vector for human gene therapy due to its favorable safety profile, versatility, and ability to transduce a wide range of tissues. However, natural AAV serotypes have shortcomings, includi...

Artificial Intelligence-Based Approaches for AAV Vector Engineering.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Adeno-associated virus (AAV) has emerged as a leading vector for gene therapy due to its broad host range, low pathogenicity, and ability to facilitate long-term gene expression. However, AAV vectors face limitations, including immunogenicity and ins...

Enhancing CRISPR-Cas9 gRNA efficiency prediction by data integration and deep learning.

Nature communications
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. ...

Overcoming Immunological Challenges Limiting Capsid-Mediated Gene Therapy With Machine Learning.

Frontiers in immunology
A key hurdle to making adeno-associated virus (AAV) capsid mediated gene therapy broadly beneficial to all patients is overcoming pre-existing and therapy-induced immune responses to these vectors. Recent advances in high-throughput DNA synthesis, mu...

Deep diversification of an AAV capsid protein by machine learning.

Nature biotechnology
Modern experimental technologies can assay large numbers of biological sequences, but engineered protein libraries rarely exceed the sequence diversity of natural protein families. Machine learning (ML) models trained directly on experimental data wi...

SemanticGO: a tool for gene functional similarity analysis in Arabidopsis thaliana and rice.

Plant science : an international journal of experimental plant biology
Gene or pathway functional similarities are important information for researchers. However, these similarities are often described sparsely and qualitatively. The latent semantic analysis of Arabidopsis thaliana (Arabidopsis) Gene Ontology (GO) data ...

Construction and characterization of recombinant adenovirus carrying a mouse TIGIT-GFP gene.

Genetics and molecular research : GMR
Recombinant adenovirus vector systems have been used extensively in protein research and gene therapy. However, the construction and characterization of recombinant adenovirus is a tedious and time-consuming process. TIGIT is a recently discovered im...

Unsupervised lineage-based characterization of primate precursors reveals high proliferative and morphological diversity in the OSVZ.

The Journal of comparative neurology
Generation of the primate cortex is characterized by the diversity of cortical precursors and the complexity of their lineage relationships. Recent studies have reported miscellaneous precursor types based on observer classification of cell biology f...