A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model.
A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model.
复制标题
基于隐马尔可夫模型的顺式调节模块识别新算法
DOI：
10.1155/2017/6274513
复制
发表时间：
2017
影响因子：
--
通讯作者：
Huo H
中科院分区：
文献类型：
--
作者：
Guo H;Huo H
顺式调控模块（CRM）的发现是理解转录调控机制的关键。由于CRM具有特定的调控结构，是基因表达调控的基础，因此如何对CRM的调控结构进行建模对CRM识别的性能具有相当大的影响。该论文提出了一种称为 ComSPS 的 CRM 发现算法。 ComSPS通过探索控制CRM内部基序位点排列的CRM转录语法规则，构建了基于HMM的CRM调控结构模型。我们在三个基准数据集上测试 ComSPS，并将其与五种现有方法进行比较。实验结果表明，ComSPS 的性能优于它们。
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 CRM identification. 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.
影响因子：
14.9
作者：
Nikulova AA;Favorov AV;Sutormin RA;Makeev VJ;Mironov AA
通讯作者：
Mironov AA