A wavelet-based method to exploit epigenomic language in the regulatory region

Nha H. Nguyen, An Vo, Kyoung Jae Won

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Motivation: Epigenetic landscapes in the regulatory regions reflect binding condition of transcription factors and their co-factors. Identifying epigenetic condition and its variation is important in understanding condition-specific gene regulation. Computational approaches to explore complex multi-dimensional landscapes are needed.Results: To study epigenomic condition for gene regulation, we developed a method, AWNFR, to classify epigenomic landscapes based on the detected epigenomic landscapes. Assuming mixture of Gaussians for a nucleosome, the proposed method captures the shape of histone modification and identifies potential regulatory regions in the wavelet domain. For accuracy estimation as well as enhanced computational speed, we developed a novel algorithm based on down-sampling operation and footprint in wavelet. We showed the algorithmic advantages of AWNFR using the simulated data. AWNFR identified regulatory regions more effectively and accurately than the previous approaches with the epigenome data in mouse embryonic stem cells and human lung fibroblast cells (IMR90). Based on the detected epigenomic landscapes, AWNFR classified epigenomic status and studied epigenomic codes. We studied co-occurring histone marks and showed that AWNFR captures the epigenomic variation across time.

Original languageEnglish (US)
Pages (from-to)908-914
Number of pages7
JournalBioinformatics
Volume30
Issue number7
DOIs
StatePublished - Apr 1 2014
Externally publishedYes

Fingerprint

Nucleic Acid Regulatory Sequences
Epigenomics
Gene expression
Wavelets
Language
Histones
Transcription factors
Gene Regulation
Fibroblasts
Stem cells
Nucleosomes
Cells
Histone Code
Sampling
Cofactor
Stem Cells
Transcription Factors
Transcription Factor
Lung
Mouse

ASJC Scopus subject areas

  • Statistics and Probability
  • Medicine(all)
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

Cite this

A wavelet-based method to exploit epigenomic language in the regulatory region. / Nguyen, Nha H.; Vo, An; Won, Kyoung Jae.

In: Bioinformatics, Vol. 30, No. 7, 01.04.2014, p. 908-914.

Research output: Contribution to journalArticle

Nguyen, Nha H. ; Vo, An ; Won, Kyoung Jae. / A wavelet-based method to exploit epigenomic language in the regulatory region. In: Bioinformatics. 2014 ; Vol. 30, No. 7. pp. 908-914.
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