AIMC Topic: Gene Editing

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Domain-specific introduction to machine learning terminology, pitfalls and opportunities in CRISPR-based gene editing.

Briefings in bioinformatics
The use of machine learning (ML) has become prevalent in the genome engineering space, with applications ranging from predicting target site efficiency to forecasting the outcome of repair events. However, jargon and ML-specific accuracy measures hav...

An Examination of Public Discourse on Human Gene Editing Using Natural Language Processing.

The CRISPR journal
This research aims to explore the different ways in which scientists, ethicists, journalists, and commissions speak to the public about new gene-editing technologies. The research collected more than 100,000 sentences from books, news articles, and r...

Revisiting CRISPR/Cas-mediated crop improvement: Special focus on nutrition.

Journal of biosciences
Genome editing (GE) technology has emerged as a multifaceted strategy that instantaneously popularised the mechanism to modify the genetic constitution of an organism. The clustered regularly interspaced short palindromic repeat (CRISPR) and CRISPR-a...

Off-target predictions in CRISPR-Cas9 gene editing using deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: The prediction of off-target mutations in CRISPR-Cas9 is a hot topic due to its relevance to gene editing research. Existing prediction methods have been developed; however, most of them just calculated scores based on mismatches to the g...