A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology.
A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology.
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DOI：
10.1038/nbt1492
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发表时间：
2008-10
影响因子：
46.9
通讯作者：
Kell, Douglas B.
中科院分区：
文献类型：
--
作者：
Herrgard, Markus J.;Swainston, Neil;Dobson, Paul;Dunn, Warwick B.;Arga, K. Yalcin;Arvas, Mikko;Bluethgen, Nils;Borger, Simon;Costenoble, Roeland;Heinemann, Matthias;Hucka, Michael;Le Novere, Nicolas;Li, Peter;Liebermeister, Wolfram;Mo, Monica L.;Oliveira, Ana Paula;Petranovic, Dina;Pettifer, Stephen;Simeonidis, Evangelos;Smallbone, Kieran;Spasic, Irena;Weichart, Dieter;Brent, Roger;Broomhead, David S.;Westerhoff, Hans V.;Kirdar, Betuel;Penttila, Merja;Klipp, Edda;Palsson, Bernhard O.;Sauer, Uwe;Oliver, Stephen G.;Mendes, Pedro;Nielsen, Jens;Kell, Douglas B.
基因组数据现在允许代谢网络的大规模手动或半自动重建。网络重建代表了一个高度策划的生物体特定的知识库。一些基因组规模的网络重建已经出现在面包酵母酿酒酵母的代谢。这些替代网络重建在范围和内容上有所不同，并且进一步使用不同的术语来描述相同的化学实体，因此难以进行比较。因此，非常需要制定一个“社区共识”网络，收集和正式化酵母代谢的“社区知识”。我们描述了我们是如何产生了一个共识代谢网络重建的S。啤酒。特别强调将分子引用到持久数据库或使用独立于数据库的形式，如SMILES或InChI字符串，因为这允许它们的化学结构被明确地表示，并以允许自动推理的方式。重建是通过一个公开访问的数据库和系统生物学标记语言，我们描述了它可以作为一个社区资源进行维护的方式。它应该作为酵母系统生物学研究的共同点。类似的策略将有利于研究其他生物体基因组规模代谢网络的社区。
Genomic data now allow the large-scale manual or semi-automated reconstruction of metabolic networks. A network reconstruction represents a highly curated organism-specific knowledge base. A few genome-scale network reconstructions have appeared for metabolism in the baker’s yeast Saccharomyces cerevisiae. These alternative network reconstructions differ in scope and content, and further have used different terminologies to describe the same chemical entities, thus making comparisons between them difficult. The formulation of a ‘community consensus’ network that collects and formalizes the ‘community knowledge’ of yeast metabolism is thus highly desirable. We describe how we have produced a consensus metabolic network reconstruction for S. cerevisiae. Special emphasis is laid on referencing molecules to persistent databases or using database-independent forms such as SMILES or InChI strings, since this permits their chemical structure to be represented unambiguously and in a manner that permits automated reasoning. The reconstruction is readily available via a publicly accessible database and in the Systems Biology Markup Language, and we describe the manner in which it can be maintained as a community resource. It should serve as a common denominator for system biology studies of yeast. Similar strategies will be of benefit to communities studying genome-scale metabolic networks of other organisms.
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代谢组数据与代谢网络的集成揭示了报告基因反应。
影响因子：
9.9
作者：
Cakir, Tunahan;Patil, Kiran Raosaheb;Onsan, Zeynep iIsen;Ulgen, Kutlu Ozergin;Kirdar, Betul;Nielsen, Jens
通讯作者：
Nielsen, Jens
影响因子：
14.9
作者：
UniProt Consortium
通讯作者：
UniProt Consortium
影响因子：
12.3
作者：
Blank LM;Kuepfer L;Sauer U
通讯作者：
Sauer U
影响因子：
30.8
作者：
Delneri, Daniela;Hoyle, David C.;Oliver, Stephen G.
通讯作者：
Oliver, Stephen G.
影响因子：
5.8
作者：
Bornstein, Benjamin J.;Keating, Sarah M.;Hucka, Michael
通讯作者：
Hucka, Michael