A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model

作者：Guo, Haitao; Huo, Hongwei^*

来源：Biomed Research International, 2017, 2017: 6274513.

DOI：10.1155/2017/6274513

• TRANSCRIPTION-FACTOR-BINDING
• GENE-REGULATION
• IDENTIFICATION
• SITES
• PREDICTION
• CLUSTERS
• MOTIFS
• DISCOVERY
• ELEMENTS
• DATABASE

The discovery of cis-regulatory modules (CRMs) is the key to understanding mechanisms of transcription regulation. Since CRMs have specific regulatory structures that are the basis for the regulation of gene expression, how to model the regulatory structure of CRMs has a considerable impact on the performance of CRMidentification. The paper proposes a CRM discovery algorithm called ComSPS. ComSPS builds a regulatory structure model of CRMs based on HMM by exploring the rules of CRM transcriptional grammar that governs the internal motif site arrangement of CRMs. We test ComSPS on three benchmark datasets and compare it with five existing methods. Experimental results show that ComSPS performs better than them.

• 出版日期2017
• 单位西安电子科技大学