iEpiCas-DL

iEpiCas-DL uses deep learning to predict sgRNA activity for CRISPR-mediated epigenome editing, optimizing sgRNA selection for targeted gene silencing or activation without altering DNA sequence.

Key Features:

• Deep learning-based prediction: Employs deep learning to predict sgRNA on-target activity and specificity from sequence and epigenetic context.
• Extensive experimental dataset: Trained on thousands of experimentally validated on-target sgRNA sites.
• Identification of influential features: Identifies sequence and epigenetic features associated with sgRNA efficacy for both gene silencing and activation.
• Optimized sgRNA selection for epigenome editing applications: Provides predictions that support selection of effective sgRNAs for CRISPR-mediated epigenome editing workflows.

Scientific Applications:

• Gene regulation studies: Supports design of sgRNAs to modulate gene expression via CRISPR-mediated epigenome editing (silencing or activation) without altering DNA sequence.
• Therapeutic research: Informs sgRNA selection for potential gene therapy strategies that aim to modulate gene expression epigenetically.

Methodology:

Trained deep learning models on a dataset of experimentally validated sgRNA on-target sites to learn relationships between sgRNA sequences, epigenetic features, and observed activity.