Discover regulatory DNA elements using chromatin signatures and artificial neural network.

ABSTRACT:

Motivation

Recent large-scale chromatin states mapping efforts have revealed characteristic chromatin modification signatures for various types of functional DNA elements. Given the important influence of chromatin states on gene regulation and the rapid accumulation of genome-wide chromatin modification data, there is a pressing need for computational methods to analyze these data in order to identify functional DNA elements. However, existing computational tools do not exploit data transformation and feature extraction as a means to achieve a more accurate prediction.

Results

We introduce a new computational framework for identifying functional DNA elements using chromatin signatures. The framework consists of a data transformation and a feature extraction step followed by

SUBMITTER: Firpi HA 

PROVIDER: S-EPMC2887052 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature