Metabolic Network Expansion with Answer Set Programming
Metabolic Network Expansion with Answer Set Programming
复制标题
通过答案集编程扩展代谢网络
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
S. Thiele
中科院分区：
文献类型：
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作者：
Torsten Schaub;S. Thiele
我们提出了一种定性方法来阐述代谢网络的生物合成能力。事实上，大规模代谢网络以及测量数据集都存在严重不完整性。此外，传统的正式生物合成方法需要动力学信息，而这种信息很少可用。我们的方法建立在分析大规模代谢网络的正式方法的基础上。将其原理映射到答案集编程 (ASP) 中使我们能够解决各种生物学相关问题。特别是，我们的方法受益于 ASP 固有的不完整性容忍能力。我们的方法得到了最近的复杂性结果的认可，表明代谢网络的重建和相关问题是 NP 困难的。
We propose a qualitative approach to elaborating the biosynthetic capacities of metabolic networks. In fact, large-scale metabolic networks as well as measured datasets suffer from substantial incompleteness. Moreover, traditional formal approaches to biosynthesis require kinetic information, which is rarely available. Our approach builds upon a formal method for analyzing large-scale metabolic networks. Mapping its principles into Answer Set Programming (ASP) allows us to address various biologically relevant problems. In particular, our approach benefits from the intrinsic incompleteness-tolerating capacities of ASP. Our approach is endorsed by recent complexity results, showing that the reconstruction of metabolic networks and related problems are NP-hard.