Photo by museumsvictoria from unsplash
We present two algorithms to predict the activity of AsCpf1 guide RNAs. Indel frequencies for 15,000 target sequences were used in a deep-learning framework based on a convolutional neural network… Click to show full abstract
We present two algorithms to predict the activity of AsCpf1 guide RNAs. Indel frequencies for 15,000 target sequences were used in a deep-learning framework based on a convolutional neural network to train Seq-deepCpf1. We then incorporated chromatin accessibility information to create the better-performing DeepCpf1 algorithm for cell lines for which such information is available and show that both algorithms outperform previous machine learning algorithms on our own and published data sets.
Keywords:
prediction crispr;
learning improves;
crispr cpf1;
deep learning;
improves prediction;
activity
Journal Title: Nature Biotechnology
Year Published: 2018
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!
Journal Title: Nature Biotechnology
Year Published: 2018
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!