Computer Science Research Works

Permanent URI for this collectionhttp://hdl.handle.net/1903/1593

Browse

Author: search.filters.author.Mount, Stephen M

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Features generated for computational splice-site prediction correspond to functional elements
    (Springer Nature, 2007-10-24) Dogan, Rezarta Islamaj; Getoor, Lise; Wilbur, W John; Mount, Stephen M
    Accurate selection of splice sites during the splicing of precursors to messenger RNA requires both relatively well-characterized signals at the splice sites and auxiliary signals in the adjacent exons and introns. We previously described a feature generation algorithm (FGA) that is capable of achieving high classification accuracy on human 3' splice sites. In this paper, we extend the splice-site prediction to 5' splice sites and explore the generated features for biologically meaningful splicing signals. We present examples from the observed features that correspond to known signals, both core signals (including the branch site and pyrimidine tract) and auxiliary signals (including GGG triplets and exon splicing enhancers). We present evidence that features identified by FGA include splicing signals not found by other methods. Our generated features capture known biological signals in the expected sequence interval flanking splice sites. The method can be easily applied to other species and to similar classification problems, such as tissue-specific regulatory elements, polyadenylation sites, promoters, etc.
  • Thumbnail Image
    Item
    Yanagi: Fast and interpretable segment-based alternative splicing and gene expression analysis
    (Springer Nature, 2019-08-13) Gunady, Mohamed K; Mount, Stephen M; Bravo, Héctor Corrada
    Ultra-fast pseudo-alignment approaches are the tool of choice in transcript-level RNA sequencing (RNA-seq) analyses. Unfortunately, these methods couple the tasks of pseudo-alignment and transcript quantification. This coupling precludes the direct usage of pseudo-alignment to other expression analyses, including alternative splicing or differential gene expression analysis, without including a non-essential transcript quantification step.