Reading between the genes: Computational models to discover function from noncoding DNA

Yves A. Lussier, Joanne Berghout, Francesca Vitali, Kenneth S. Ramos, Maricel Kann, Jason H. Moore

Research output: Contribution to journalConference articlepeer-review

Abstract

Noncoding DNA-once called “junk” has revealed itself to be full of function. Technology development has allowed researchers to gather genome-scale data pointing towards complex regulatory regions, expression and function of noncoding RNA genes, and conserved elements. Variation in these regions has been tied to variation in biological function and human disease. This PSB session tackles the problem of handling, analyzing and interpreting the data relating to variation in and interactions between noncoding regions through computational biology. We feature an invited speaker to how variation in transcription factor coding sequences impacts on sequence preference, along with submitted papers that span graph based methods, integrative analyses, machine learning, and dimension reduction to explore questions of basic biology, cancer, diabetes, and clinical relevance.

Original languageEnglish (US)
Pages (from-to)507-511
Number of pages5
JournalPacific Symposium on Biocomputing
Volume0
Issue number212669
DOIs
StatePublished - 2018
Event23rd Pacific Symposium on Biocomputing, PSB 2018 - Kohala Coast, United States
Duration: Jan 3 2018Jan 7 2018

Keywords

  • Intergenic
  • LINE1
  • LINEs
  • LncRNA
  • MiRNA
  • MicroRNA
  • Non-coding DNA
  • PiRNA
  • Repetitive elements
  • SncRNA

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computational Theory and Mathematics

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