ENCODE GRAMMAR: 3865-dataset seq2func model collection decodes regulatory DNA sequence logic
anshulkundaje · x · 2026-10-15
Stanford PhD candidate Chang Yun will present ENCODE GRAMMAR at the BioML Seminar at UC Berkeley (Oct 19) — one of the largest collections of regulatory DNA sequence-to-function models to date.
- While the ENCODE Project has mapped millions of functional regulatory regions across human and mouse genomes over two decades, the maps don't fully explain how regulatory activity is encoded in the DNA sequence itself: which bases matter, how sequence arrangements drive cell-type-specific behavior, or how variants alter activity.
- ENCODE GRAMMAR (Genomic Regulatory Atlas of sequence Models, Motifs, Annotations and Rules) spans 3,865 experiment datasets covering multiple layers of gene regulation.
- Accompanying interpretation frameworks identify the sequence features and rules driving predictions, and show how predictions from multiple models and modalities can be integrated to decode regulatory sequence logic.
Related event: Stanford Unveils ENCODE GRAMMAR: 3,865 Datasets Decoding Regulatory DNA(2 posts)→
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