AIMC Topic: Gene Editing

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Monoclonal antibodies production in microbial systems: Current status, challenges and perspectives.

New biotechnology
Monoclonal antibodies (mAbs) serve as indispensable tools in diagnostics, clinical therapeutics, and biomedical research. However, their large-scale production faces significant challenges due to the high costs and lengthy timelines associated with c...

Bio-digital feedback loop systems: a synergistic integration of predictive genomics, genome editing, and AI-driven phenomic synthesis for next-generation edible and medicinal mushroom breeding.

Antonie van Leeuwenhoek
Edible mushrooms face persistent challenges in yield optimization, bioactive compound production, and climate resilience that conventional breeding methods struggle to address. Traditional approaches such as cross-breeding, protoplast fusion, and mut...

Recent advances in breeding systems and their improvement in forage crops.

Molecular biology reports
Fodder crops are crops which are mainly grown as feed for livestocks and it consist of a variety of crops ranging from annual to perennial crops. Even with many crops involved, advance crop improvement practices are done less in these crops. With the...

Revolution and advances in gene editing and genomics technology for developing climate-resilient legume crops: developments and prospects.

Plant molecular biology
Legumes are essential for agriculture and food security. Biotic and abiotic stresses pose significant challenges to legume production, lowering productivity levels. Most legumes must be genetically improved by introducing alleles that give pest and d...

Prime editor with rational design and AI-driven optimization for reverse editing window and enhanced fidelity.

Nature communications
Prime editing (PE) is a precise tool for introducing genetic mutations in eukaryotes. Extending the efficient editing scope and mitigating undesired byproducts are possible. We introduce reverse PE (rPE), a SpCas9-directed variant that enabled DNA ed...

CRISPR-MFH: A Lightweight Hybrid Deep Learning Framework with Multi-Feature Encoding for Improved CRISPR-Cas9 Off-Target Prediction.

Genes
BACKGROUND: The CRISPR-Cas9 system has emerged as one of the most promising gene-editing technologies in biology. However, off-target effects remain a significant challenge. While recent advances in deep learning have led to the development of models...

Adapting systems biology to address the complexity of human disease in the single-cell era.

Nature reviews. Genetics
Systems biology aims to achieve holistic insights into the molecular workings of cellular systems through iterative loops of measurement, analysis and perturbation. This framework has had remarkable success in unicellular model organisms, and recent ...

Engineering a New Generation of Gene Editors: Integrating Synthetic Biology and AI Innovations.

ACS synthetic biology
CRISPR-Cas technology has revolutionized biology by enabling precise DNA and RNA edits with ease. However, significant challenges remain for translating this technology into clinical applications. Traditional protein engineering methods, such as rati...

Transitioning from wet lab to artificial intelligence: a systematic review of AI predictors in CRISPR.

Journal of translational medicine
The revolutionary CRISPR-Cas9 system leverages a programmable guide RNA (gRNA) and Cas9 proteins to precisely cleave problematic regions within DNA sequences. This groundbreaking technology holds immense potential for the development of targeted ther...

Protocol for functional screening of CFTR-targeted genetic therapies in patient-derived organoids using DETECTOR deep-learning-based analysis.

STAR protocols
Here, we present a protocol for the rapid functional screening of gene editing and addition strategies in patient-derived organoids using the deep-learning-based tool DETECTOR (detection of targeted editing of cystic fibrosis transmembrane conductanc...