ProOpDB: Prokaryotic Operon DataBase.

ProOpDB: Prokaryotic Operon DataBase.
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DOI:
10.1093/nar/gkr1020
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发表时间:
2012-01
影响因子:
14.9
通讯作者:
Merino E
Merino E
中科院分区:
生物学2区
文献类型:
--
作者:
Taboada B;Ciria R;Martinez-Guerrero CE;Merino E

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原核生物操纵子数据库(ProOpDB,http://operons.ibt.unam.mx/OperonPredictor))构成了目前可用的最精确和最完整的操纵子预测库之一。使用我们新颖且高精度的操纵子识别算法,我们已经预测了1200多个原核生物基因组的操纵子结构。ProOpDB提供了多种替代方案,可用于检索一组操纵子预测,包括:(I)生物体名称,(Ii)KEGG数据库定义的代谢途径,(Iii)COG数据库定义的基因正构学,(Iv)Pfam数据库定义的保守蛋白质结构域,(V)参考基因和(Vi)参考操纵子,等等。为了将操纵子的输出限制为非冗余生物,ProOpDB提供了一种基于预先编制的系统发育距离矩阵来选择最具代表性的生物的有效方法。此外,ProOpDB操纵子预测直接用作我们的基因上下文工具的输入数据,以可视化它们的基因组上下文,并检索它们相应的5‘调节区的序列,以及它们基因的核苷酸或氨基酸序列。
The Prokaryotic Operon DataBase (ProOpDB, http://operons.ibt.unam.mx/OperonPredictor) constitutes one of the most precise and complete repositories of operon predictions now available. Using our novel and highly accurate operon identification algorithm, we have predicted the operon structures of more than 1200 prokaryotic genomes. ProOpDB offers diverse alternatives by which a set of operon predictions can be retrieved including: (i) organism name, (ii) metabolic pathways, as defined by the KEGG database, (iii) gene orthology, as defined by the COG database, (iv) conserved protein domains, as defined by the Pfam database, (v) reference gene and (vi) reference operon, among others. In order to limit the operon output to non-redundant organisms, ProOpDB offers an efficient method to select the most representative organisms based on a precompiled phylogenetic distances matrix. In addition, the ProOpDB operon predictions are used directly as the input data of our Gene Context Tool to visualize their genomic context and retrieve the sequence of their corresponding 5′ regulatory regions, as well as the nucleotide or amino acid sequences of their genes.
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