期刊
INDUCTIVE LOGIC PROGRAMMING, ILP 2014
卷 9046, 期 -, 页码 33-48出版社
SPRINGER-VERLAG BERLIN
DOI: 10.1007/978-3-319-23708-4_3
关键词
ILP; ALP; ASP; Metabolic networks; Completion; Revision
类别
资金
- EPSRC [EP/K035959/1] Funding Source: UKRI
This paper introduces a new open-source implementation of a nonmonotonic learning method called XHAIL and shows how it can be used for abductive and inductive inference on metabolic networks that are many times larger than could be handled by the preceding prototype. We summarise several implementation improvements that increase its efficiency and we introduce an extended form of language bias that further increases its usability. We investigate the system's scalability in a case study involving real data previously collected by a Robot Scientist and show how it led to the discovery of an error in a whole-organism model of yeast metabolism.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据