Predictor of Deletions after Targeted Chromosome Cleavage

The specification provides a machine-learning model which predicts, based on input that can include a given target DNA sequence and a CRISPR/Cas cut site location, repair genotype outcomes associated with template-free repair processes (e.g., MMEJ or NHEJ) acting on Cas9- induced double- stranded DNA breaks. The specification further provides for the use of a machine-learning model for conducting genome editing based on a template-free CRISPR/Cas system, including the selection of an appropriate guide RNA (gRNA) to achieve a desired repaired genotype outcome.

Researchers

Max Shen / Jonathan Hsu / David Gifford

Departments: Dept of Electrical Engineering & Computer Science
Technology Areas: Biotechnology: DNA & RNA Editing / Computer Science: Bioinformatics

  • systems and methods for predicting repair outcomes in genetic engineering
    Patent Cooperation Treaty | Published application

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