Latent Dirichlet allocation mixture models for nucleotide sequence analysis
Bixuan Wang,
Stephen M Mount
Abstract:Strings of nucleotides carrying biological information are typically described as sequence motifs represented by weight matrices or consensus sequences. However, many signals in DNA or RNA are recognized by multiple factors in temporal sequence, consist of distinct alternative motifs, or are best described by base composition. Here we apply the latent Dirichlet allocation (LDA) mixture model to nucleotide sequences. Using positions in an alignment of human or Drosophila splice sites as samples, we show that LD… Show more
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