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MatrixCatch--一种用于识别启动子中复合调控元件的新型工具。

MatrixCatch--a novel tool for the recognition of composite regulatory elements in promoters.

机构信息

Department of Molecular Immunology, Helmholtz Centre for Infection Research, Braunschweig, Germany.

出版信息

BMC Bioinformatics. 2013 Aug 8;14:241. doi: 10.1186/1471-2105-14-241.

Abstract

BACKGROUND

Accurate recognition of regulatory elements in promoters is an essential prerequisite for understanding the mechanisms of gene regulation at the level of transcription. Composite regulatory elements represent a particular type of such transcriptional regulatory elements consisting of pairs of individual DNA motifs. In contrast to the present approach, most available recognition techniques are based purely on statistical evaluation of the occurrence of single motifs. Such methods are limited in application, since the accuracy of recognition is greatly dependent on the size and quality of the sequence dataset. Methods that exploit available knowledge and have broad applicability are evidently needed.

RESULTS

We developed a novel method to identify composite regulatory elements in promoters using a library of known examples. In depth investigation of regularities encoded in known composite elements allowed us to introduce a new characteristic measure and to improve the specificity compared with other methods. Tests on an established benchmark and real genomic data show that our method outperforms other available methods based either on known examples or statistical evaluations. In addition to better recognition, a practical advantage of this method is first the ability to detect a high number of different types of composite elements, and second direct biological interpretation of the identified results. The program is available at http://gnaweb.helmholtz-hzi.de/cgi-bin/MCatch/MatrixCatch.pl and includes an option to extend the provided library by user supplied data.

CONCLUSIONS

The novel algorithm for the identification of composite regulatory elements presented in this paper was proved to be superior to existing methods. Its application to tissue specific promoters identified several highly specific composite elements with relevance to their biological function. This approach together with other methods will further advance the understanding of transcriptional regulation of genes.

摘要

背景

准确识别启动子中的调控元件是理解转录水平基因调控机制的必要前提。复合调控元件是一种特殊类型的转录调控元件,由一对单个 DNA 基序组成。与目前的方法不同,大多数可用的识别技术纯粹基于单个基序出现的统计评估。由于识别的准确性在很大程度上取决于序列数据集的大小和质量,因此这些方法的应用受到限制。显然需要利用现有知识且具有广泛适用性的方法。

结果

我们开发了一种使用已知实例库识别启动子中复合调控元件的新方法。对已知复合元件中编码的规律进行深入研究,使我们能够引入新的特征度量,并与其他方法相比提高了特异性。在已建立的基准测试和真实基因组数据上的测试表明,我们的方法优于其他基于已知示例或统计评估的可用方法。除了更好的识别外,这种方法的一个实际优点是:首先,能够检测到大量不同类型的复合元件;其次,可以直接对识别结果进行生物学解释。该程序可在 http://gnaweb.helmholtz-hzi.de/cgi-bin/MCatch/MatrixCatch.pl 上获得,并包括一个选项,可通过用户提供的数据扩展提供的库。

结论

本文提出的用于识别复合调控元件的新算法被证明优于现有方法。将其应用于组织特异性启动子,鉴定了几种与生物学功能相关的高度特异性复合元件。这种方法与其他方法相结合将进一步推进对基因转录调控的理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8325/3754795/c73bac80069f/1471-2105-14-241-1.jpg

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