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

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

SUBMITTER: Nguyen N 

PROVIDER: S-EPMC3983404 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature