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PromAn:一个致力于启动子分析的基于知识的集成网络服务器。

PromAn: an integrated knowledge-based web server dedicated to promoter analysis.

作者信息

Lardenois Aurélie, Chalmel Frédéric, Bianchetti Laurent, Sahel José-Alain, Léveillard Thierry, Poch Olivier

机构信息

Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire, CNRS/INSERM/ULP, BP 163, 67404 Illkirch Cedex, France.

出版信息

Nucleic Acids Res. 2006 Jul 1;34(Web Server issue):W578-83. doi: 10.1093/nar/gkl193.

Abstract

PromAn is a modular web-based tool dedicated to promoter analysis that integrates distinct complementary databases, methods and programs. PromAn provides automatic analysis of a genomic region with minimal prior knowledge of the genomic sequence. Prediction programs and experimental databases are combined to locate the transcription start site (TSS) and the promoter region within a large genomic input sequence. Transcription factor binding sites (TFBSs) can be predicted using several public databases and user-defined motifs. Also, a phylogenetic footprinting strategy, combining multiple alignment of large genomic sequences and assignment of various scores reflecting the evolutionary selection pressure, allows for evaluation and ranking of TFBS predictions. PromAn results can be displayed in an interactive graphical user interface, PromAnGUI. It integrates all of this information to highlight active promoter regions, to identify among the huge number of TFBS predictions those which are the most likely to be potentially functional and to facilitate user refined analysis. Such an integrative approach is essential in the face of a growing number of tools dedicated to promoter analysis in order to propose hypotheses to direct further experimental validations. PromAn is publicly available at http://bips.u-strasbg.fr/PromAn.

摘要

PromAn是一个基于网络的模块化工具,致力于启动子分析,它整合了不同的互补数据库、方法和程序。PromAn在对基因组序列仅有极少先验知识的情况下,就能对基因组区域进行自动分析。预测程序和实验数据库相结合,可在大型基因组输入序列中定位转录起始位点(TSS)和启动子区域。转录因子结合位点(TFBS)可通过多个公共数据库和用户定义的基序进行预测。此外,一种系统发育足迹策略,结合大型基因组序列的多重比对和反映进化选择压力的各种得分的分配,可对TFBS预测进行评估和排序。PromAn的结果可在交互式图形用户界面PromAnGUI中显示。它整合了所有这些信息,以突出活跃的启动子区域,在大量的TFBS预测中识别出最有可能具有潜在功能的预测,并便于用户进行精细分析。面对越来越多致力于启动子分析的工具,这种综合方法对于提出假设以指导进一步的实验验证至关重要。PromAn可在http://bips.u-strasbg.fr/PromAn上公开获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03c7/1538850/fa5141351e5f/gkl193f1.jpg

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