PathPred: an enzyme-catalyzed metabolic pathway prediction server.

PathPred: an enzyme-catalyzed metabolic pathway prediction server.
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DOI:
10.1093/nar/gkq318
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发表时间:
2010-07
影响因子:
14.9
通讯作者:
Kanehisa M
Kanehisa M
中科院分区:
生物学2区
文献类型:
--
作者:
Moriya Y;Shigemizu D;Hattori M;Tokimatsu T;Kotera M;Goto S;Kanehisa M

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KEGG RPAIR数据库是一个生化结构转化模式(称为RDM模式)和所有已知酶催化反应中底物-产物对(反应物对)化学结构比对的集合,这些数据来自酶Nomenclature和KEGG PATHWAY数据库。在这里,我们提出了PathPred(http://www.genome.jp/tools/pathpred/),一个基于Web的服务器来预测从查询化合物开始的多步反应的可能途径,基于本地RDM模式匹配和全局化学结构比对对反应物对库。在这个服务器中,我们专注于预测环境化合物的微生物生物降解和植物次生代谢产物的生物合成途径,这分别对应于947和1397反应物对的特征RDM模式。服务器提供每个预测反应中的转化化合物和参考转化模式,并在树形图中显示所有预测的多步反应途径。
The KEGG RPAIR database is a collection of biochemical structure transformation patterns, called RDM patterns, and chemical structure alignments of substrate-product pairs (reactant pairs) in all known enzyme-catalyzed reactions taken from the Enzyme Nomenclature and the KEGG PATHWAY database. Here, we present PathPred (http://www.genome.jp/tools/pathpred/), a web-based server to predict plausible pathways of muti-step reactions starting from a query compound, based on the local RDM pattern match and the global chemical structure alignment against the reactant pair library. In this server, we focus on predicting pathways for microbial biodegradation of environmental compounds and biosynthesis of plant secondary metabolites, which correspond to characteristic RDM patterns in 947 and 1397 reactant pairs, respectively. The server provides transformed compounds and reference transformation patterns in each predicted reaction, and displays all predicted multi-step reaction pathways in a tree-shaped graph.
DOI: 10.1093/bioinformatics/btp223
发表时间: 2009-06-15
期刊: Bioinformatics (Oxford, England)
影响因子: --
作者:
Yamanishi Y;Hattori M;Kotera M;Goto S;Kanehisa M
通讯作者: Kanehisa M
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发表时间: 2010-01
影响因子: 14.9
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