Basenji
A deep learning toolkit for predicting regulatory activity, 3D genome folding, and mRNA half-life from DNA/RNA sequences.
What is Basenji?
Basenji is a deep learning toolkit for functional genomics that predicts regulatory activity, 3D genome folding, and mRNA half-life from DNA and RNA sequences. It enables researchers to model gene regulation at chromosome scale, annotate regulatory elements, and score genetic variants for their functional impact. The toolkit includes specialized models like Akita for genome folding and Saluki for mRNA stability.
Bioinformatics researchers and computational biologists studying gene regulation, variant effects, and genome architecture who need scalable deep learning models for sequence-based predictions.
Developers choose Basenji for its ability to handle very long chromosome-scale sequences, its quantitative regression approach, and its integration of multiple prediction tasks (regulatory activity, 3D folding, mRNA stability) in one toolkit. It offers improvements over predecessor Basset with TensorFlow support and greater flexibility.
Overview
Sequential regulatory activity predictions with deep convolutional neural networks.
Use Cases
Best For
- Training deep convolutional networks to predict regulatory activity across long DNA sequences
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