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. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Schaub, T., & Thiele, S. (2009). Metabolic network expansion with answer set programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5649 LNCS, pp. 312–326). https://doi.org/10.1007/978-3-642-02846-5_27
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