A deep learning model for predicting CRISPR-Cas9 editing efficiency based on DNA sequences and epigenetic features. This model integrates sequence data and epigenetic signals to provide highly accurate predictions of CRISPR editing efficiency.
Model Details
Model Type: Convolutional Neural Network (CNN)
Input Features:
DNA Sequence: 23-base target sequence, one-hot encoded.
Epigenetic Features:
CTCF (Transcription factor binding sites)
DNase (Chromatin accessibility)
H3K4me3 (Histone modification marker)
RRBS (Methylation marker)
Output: A single efficiency score indicating the likelihood of successful CRISPR editing for the given input.
