Expansion of the BioCyc collection of pathway/genome databases to 160 genomes.
Expansion of the BioCyc collection of pathway/genome databases to 160 genomes.
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DOI：
10.1093/nar/gki892
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发表时间：
2005
影响因子：
14.9
通讯作者：
López-Bigas N
中科院分区：
文献类型：
--
作者：
Karp PD;Ouzounis CA;Moore-Kochlacs C;Goldovsky L;Kaipa P;Ahrén D;Tsoka S;Darzentas N;Kunin V;López-Bigas N
BioCyc 数据库集合是一组 160 个途径/基因组数据库 (PGDB)，适用于大多数真核和原核物种，其基因组迄今为止已完全测序。 BioCyc 集合中的每个 PGDB 描述了从 MetaCyc 数据库推断出的单个生物体的基因组和预测的代谢网络，MetaCyc 数据库是多个生物体代谢途径的参考来源。此外，每个细菌 PGDB 都包含相应物种的预测操纵子。 BioCyc 集合为计算系统生物学提供了独特的资源，即基因组和代谢网络的全局和比较分析，以及对策划的 PGDB BioCyc 资源的补充。 BioCyc 网站上提供的组学查看器使科学家能够在这些生物体的代谢图上可视化基因表达、蛋白质组学和代谢组学数据的组合。本文讨论了 BioCyc 集合扩展的计算方法，并对集合进行了聚合分析，其中包括这些生物体中存在的途径数量范围以及最常观察到的途径。我们寻求科学家在 BioCyc 系列中采用和管理单个 PGDB。只有通过利用许多科学家的专业知识，我们才有希望创建生物数据库，准确地反映生物医学研究界正在产生的知识的深度和广度。
The BioCyc database collection is a set of 160 pathway/genome databases (PGDBs) for most eukaryotic and prokaryotic species whose genomes have been completely sequenced to date. Each PGDB in the BioCyc collection describes the genome and predicted metabolic network of a single organism, inferred from the MetaCyc database, which is a reference source on metabolic pathways from multiple organisms. In addition, each bacterial PGDB includes predicted operons for the corresponding species. The BioCyc collection provides a unique resource for computational systems biology, namely global and comparative analyses of genomes and metabolic networks, and a supplement to the BioCyc resource of curated PGDBs. The Omics viewer available through the BioCyc website allows scientists to visualize combinations of gene expression, proteomics and metabolomics data on the metabolic maps of these organisms. This paper discusses the computational methodology by which the BioCyc collection has been expanded, and presents an aggregate analysis of the collection that includes the range of number of pathways present in these organisms, and the most frequently observed pathways. We seek scientists to adopt and curate individual PGDBs within the BioCyc collection. Only by harnessing the expertise of many scientists we can hope to produce biological databases, which accurately reflect the depth and breadth of knowledge that the biomedical research community is producing.
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影响因子：
5.8
作者：
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通讯作者：
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