Cited by 29Chromosomal and Genetic VariationsGenomics and Phylogenetic StudiesFractal and DNA sequence analysis

Identifying centromeric satellites with dna-brnn

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Li, Heng·2019·Bioinformatics

Abstract

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 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

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Crossref · 10.1093/bioinformatics/btz264

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  • dna-brnn uses a recurrent neural network to identify alpha satellites as well as human satellites 1 and 2.

    “dna-brnn is a tool that uses a recurrent neural network to quickly identify alpha satellites as well as human satellites 1 and 2 (ref. 90).”

    From A draft human pangenome reference. (2023) · cites this paper as [90]

    The Introduction and §2.1 say dna-brnn uses a recurrent neural network to identify alpha satellite (alphoid) and human satellite II/III (hsat2,3). The claim is correct about the method and alpha satellite, but names satellites 1 and 2 rather than the paper’s satellites 2 and 3. (LLM, conf=0.90)

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Authors
Li, H.
Affiliations
Harvard University (US)
Corresponding author
Li, Heng
Venue
Bioinformatics
Published
2019-04-15
Volume
35
Issue
21
Pages
4408-4410
ISSN
  • 1367-4803 (ISSN-L)
  • 1367-4811
OpenAlex
W2962988145
Cited by
28
References
10
Citations by year
2026: 3 · 2025: 3 · 2024: 2 · 2023: 9 · 2022: 2 · 2021: 4 · 2020: 4 · 2019: 1
FWCI
2.03
Type
journal article
Language
en
Open access
Locations
  • Bioinformatics (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Funders
NHGRI (R01-HG010040)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Chromosomal and Genetic Variations
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fractal and DNA sequence analysis
Keywords
alpha satellite, centromeric repeats, DNA sequence classification, recurrent neural networks, DNA sequence prediction, human genome
MeSH terms
Algorithms, Centromere, DNA, Satellite, Humans, Genome, Human, Neural Networks, Computer

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