MP-Align: alignment of metabolic pathways.
MP-Align: alignment of metabolic pathways.
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DOI：
10.1186/1752-0509-8-58
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发表时间：
2014-05-20
影响因子：
--
通讯作者：
Tuduri M
中科院分区：
文献类型：
--
作者：
Alberich R;Llabrés M;Sánchez D;Simeoni M;Tuduri M
比较不同物种的代谢途径有助于了解代谢功能，有助于研究疾病和工程药物。文献中已经介绍了几种代谢途径的比较技术，作为这个方向的首次尝试。这些方法基于代谢途径的一些简化表示以及两条途径之间相似性得分（或距离度量）的相关定义。最近的比较研究侧重于可以识别路径之间相似部分的对齐技术。我们提出了一种代谢途径的成对比较和比对方法，旨在提供所考虑途径的最大保守子结构。所提出的方法已在名为 MP-Align 的工具中实施，该工具已用于执行多项验证测试。结果表明，我们的相似性评分使得区分不同领域并从代谢数据重建有意义的系统发育成为可能。结果进一步证明我们的比对算法正确识别了具有共同生物学功能的子路径。使用 MP-Align 进行的验证测试结果令人鼓舞。与文献中的另一个提案的比较表明，我们的比对算法特别适合寻找所检查路径中最大的保守子路径。
Comparing the metabolic pathways of different species is useful for understanding metabolic functions and can help in studying diseases and engineering drugs. Several comparison techniques for metabolic pathways have been introduced in the literature as a first attempt in this direction. The approaches are based on some simplified representation of metabolic pathways and on a related definition of a similarity score (or distance measure) between two pathways. More recent comparative research focuses on alignment techniques that can identify similar parts between pathways. We propose a methodology for the pairwise comparison and alignment of metabolic pathways that aims at providing the largest conserved substructure of the pathways under consideration. The proposed methodology has been implemented in a tool called MP-Align, which has been used to perform several validation tests. The results showed that our similarity score makes it possible to discriminate between different domains and to reconstruct a meaningful phylogeny from metabolic data. The results further demonstrate that our alignment algorithm correctly identifies subpathways sharing a common biological function. The results of the validation tests performed with MP-Align are encouraging. A comparison with another proposal in the literature showed that our alignment algorithm is particularly well-suited to finding the largest conserved subpathway of the pathways under examination.
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影响因子：
3.7
作者：
Qian X;Yoon BJ
通讯作者：
Yoon BJ
影响因子：
--
作者：
Li Y;de Ridder D;de Groot MJ;Reinders MJ
通讯作者：
Reinders MJ
影响因子：
5.8
作者：
Clemente, Jose C.;Satou, Kenji;Valiente, Gabriel
通讯作者：
Valiente, Gabriel
Isorankn：多个蛋白质网络全局对齐的光谱方法。
DOI：
10.1093/bioinformatics/btp203
发表时间：
2009-06-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Liao CS;Lu K;Baym M;Singh R;Berger B
通讯作者：
Berger B
影响因子：
5.8
作者：
Kalaev, Maxim;Smoot, Mike;Sharan, Roded
通讯作者：
Sharan, Roded