Papers › Identifying centromeric satellites with dna-brnn
Identifying centromeric satellites with dna-brnn
Heng Li
Summary: Human alpha satellite and satellite 2/3 contribute to several percent of the human genome. However, identifying these sequences with traditional algorithms is computationally intensive. Here we develop dna-brnn, a recurrent neural network to learn the sequences of the two classes of centromeric repeats. It achieves high similarity to RepeatMasker and is tens of times faster. Dna-brnn explores a novel application of deep learning and may accelerate the study of the evolution of the two repeat classes. Availability and implementation: https://github.com/lh3/dna-nn Contact: hli@jimmy.harvard.edu
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections