An Entropy-Based Position Projection Algorithm for Motif Discovery. (2nd November 2016)

• Record Type: Journal Article
• Authors: Zhang, Yipu; Wang, Ping; Yan, Maode
• Other Names: Sun Zhirong Academic Editor.
• Is Part Of: BioMed research international. Volume 2016(2016)
• Publication Date: 2016-11-02
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Life sciences -- Periodicals; 610.5
• DOI: 10.1155/2016/9127474
• Languages: English
• ISSNs: 2314-6133

Abstract

Abstract : Motif discovery problem is crucial for understanding the structure and function of gene expression. Over the past decades, many attempts using consensus and probability training model for motif finding are successful. However, the most existing motif discovery algorithms are still time-consuming or easily trapped in a local optimum. To overcome these shortcomings, in this paper, we propose an entropy-based position projection algorithm, called EPP, which designs a projection process to divide the dataset and explores the best local optimal solution. The experimental results on real DNA sequences, Tompa data, and ChIP-seq data show that EPP is advantageous in dealing with the motif discovery problem and outperforms current widely used algorithms.